8.6.1 Instance Segmentation

Chapter Contents (Back)
Segmentation, Guided. Segmentation, Instance. Instance Segmentation.
See also Counting Instances, Counting Objects.
See also Video Instance Segmentation.
See also Instance Segmentation, Point Cloud Segmentation.
See also Object Localization.
See also Panoptic Segmentation.

Harwood, D.A., Chang, S., and Davis, L.S.,
Interpreting Aerial Photographs by Segmentation and Search,
DARPA87(507-520). (
See also Sigma Image Understanding System, The. ) Find segments (homogeneous regions), then find instances which satisfy definitions of object types, then search for support, then improve instances, then iterate with new estimates of parameters.
See also Fua and Leclerc Guided Segmentation Papers. BibRef 8700

Meng, J., Yuan, J., Yang, J., Wang, G., Tan, Y.P.,
Object Instance Search in Videos via Spatio-Temporal Trajectory Discovery,
MultMed(18), No. 1, January 2016, pp. 116-127.
IEEE DOI 1601
Find specific object. BibRef

Wang, L.T.[Lian-Tao], Meng, D., Hu, X.L.[Xue-Lei], Lu, J.F.[Jian-Feng], Zhao, J.[Ji],
Instance Annotation via Optimal BoW for Weakly Supervised Object Localization,
Cyber(47), No. 5, May 2017, pp. 1313-1324.
IEEE DOI 1704
BibRef
Earlier: A1, A5, A3, A4, Only:
Weakly supervised object localization via maximal entropy randomwalk,
ICIP14(1614-1617)
IEEE DOI 1502
Birds. Entropy BibRef

Yu, J.G.[Jin-Gang], Li, Y.S.[Yan-Sheng], Gao, C.X.[Chang-Xin], Gao, H.X.[Hong-Xia], Xia, G.S.[Gui-Song], Yu, Z.L.[Zhu Liang], Li, Y.Q.[Yuan-Qing],
Exemplar-Based Recursive Instance Segmentation With Application to Plant Image Analysis,
IP(29), No. 1, 2020, pp. 389-404.
IEEE DOI 1910
biology computing, computational complexity, image classification, image segmentation, inference mechanisms, plant phenotyping BibRef

Zhang, H., Tian, Y., Wang, K., Zhang, W., Wang, F.,
Mask SSD: An Effective Single-Stage Approach to Object Instance Segmentation,
IP(29), 2020, pp. 2078-2093.
IEEE DOI 2001
Object detection, instance segmentation, feedback features, single-shot detector BibRef

Goldman, E.[Eran], Goldberger, J.[Jacob],
CRF with deep class embedding for large scale classification,
CVIU(191), 2020, pp. 102865.
Elsevier DOI 2002
CRF, Class embedding, Matrix factorization, Surrogate likelihood, Batch normalization BibRef

Goldman, E.[Eran], Herzig, R.[Roei], Eisenschtat, A.[Aviv], Goldberger, J.[Jacob], Hassner, T.[Tal],
Precise Detection in Densely Packed Scenes,
CVPR19(5222-5231).
IEEE DOI 2002
E.g. man-made scenes with numerous identical objects. BibRef

Su, H.[Hao], Wei, S.J.[Shun-Jun], Liu, S.[Shan], Liang, J.D.[Jia-Dian], Wang, C.[Chen], Shi, J.[Jun], Zhang, X.L.[Xiao-Ling],
HQ-ISNet: High-Quality Instance Segmentation for Remote Sensing Imagery,
RS(12), No. 6, 2020, pp. xx-yy.
DOI Link 2003
BibRef

Grard, M.[Matthieu], Dellandréa, E.[Emmanuel], Chen, L.M.[Li-Ming],
Deep Multicameral Decoding for Localizing Unoccluded Object Instances from a Single RGB Image,
IJCV(128), No. 5, May 2020, pp. 1331-1359.
Springer DOI 2005
BibRef

Oba, T.[Takeru], Ukita, N.[Norimichi],
Instance Segmentation by Semi-Supervised Learning and Image Synthesis,
IEICE(E103-D), No. 6, June 2020, pp. 1247-1256.
WWW Link. 2006
BibRef

Hafiz, A.M.[Abdul Mueed], Bhat, G.M.[Ghulam Mohiuddin],
A survey on instance segmentation: state of the art,
MultInfoRetr(9), No. 3, September 2020, pp. 171-189.
WWW Link. 2008
BibRef

Kim, N.[Nuri], Lee, D.[Donghoon], Oh, S.H.[Song-Hwai],
Learning instance-aware object detection using determinantal point processes,
CVIU(201), 2020, pp. 103061.
Elsevier DOI 2011
Determinantal Point Processes, Object Detection, Crowd Detection BibRef

Hu, Z.[Zheng], Liu, Z.[Zhi], Li, G.Y.[Gong-Yang], Ye, L.W.[Lin-Wei], Zhou, L.[Lei], Wang, Y.[Yang],
Weakly supervised instance segmentation using multi-stage erasing refinement and saliency-guided proposals ordering,
JVCIR(73), 2020, pp. 102957.
Elsevier DOI 2012
Weakly supervised instance segmentation, Image-level annotations, Multi-stage erasing refinement, Saliency-guided proposals ordering BibRef

Feng, D.[Dong], Liang, M.G.[Man-Gui], Gao, F.[Feng], Huang, Y.C.[Yi-Cheng], Zhang, X.F.[Xin-Feng], Duan, L.Y.[Ling-Yu],
Towards Large-Scale Object Instance Search: A Multi-Block N-Ary Trie,
CirSysVideo(31), No. 1, January 2021, pp. 372-386.
IEEE DOI 2101
Veins, Binary codes, Search problems, Computational efficiency, Task analysis, Optimization, Indexing, Object search, binary code, approximate nearest neighbor (ANN) search BibRef

Ferreira de Carvalho, O.L.[Osmar Luiz], de Carvalho Júnior, O.A.[Osmar Abílio], de Albuquerque, A.O.[Anesmar Olino], de Bem, P.P.[Pablo Pozzobon], Silva, C.R.[Cristiano Rosa], Ferreira, P.H.G.[Pedro Henrique Guimarães], dos Santos de Moura, R.[Rebeca], Gomes, R.A.T.[Roberto Arnaldo Trancoso], Guimarães, R.F.[Renato Fontes], Borges, D.L.[Díbio Leandro],
Instance Segmentation for Large, Multi-Channel Remote Sensing Imagery Using Mask-RCNN and a Mosaicking Approach,
RS(13), No. 1, 2021, pp. xx-yy.
DOI Link 2101
BibRef

Liu, D., Zhang, D., Song, Y., Huang, H., Cai, W.,
Panoptic Feature Fusion Net: A Novel Instance Segmentation Paradigm for Biomedical and Biological Images,
IP(30), 2021, pp. 2045-2059.
IEEE DOI 2101
Semantics, Image segmentation, Task analysis, Biology, Biomedical imaging, Computer architecture, Histopathology, plant phenotype images BibRef

Chen, L.W.[Lin-Wei], Fu, Y.[Ying], You, S.[Shaodi], Liu, H.Z.[Hong-Zhe],
Efficient Hybrid Supervision for Instance Segmentation in Aerial Images,
RS(13), No. 2, 2021, pp. xx-yy.
DOI Link 2101
BibRef

Gao, N.Y.[Nai-Yu], Shan, Y.H.[Yan-Hu], Wang, Y.P.[Yu-Pei], Zhao, X.[Xin], Huang, K.Q.[Kai-Qi],
SSAP: Single-Shot Instance Segmentation With Affinity Pyramid,
CirSysVideo(31), No. 2, February 2021, pp. 661-673.
IEEE DOI 2102
Semantics, Image segmentation, Training, Proposals, Task analysis, Automation, Predictive models, Instance segmentation, graph partition BibRef

Gao, N.Y.[Nai-Yu], Shan, Y.H.[Yan-Hu], Wang, Y.P.[Yu-Pei], Zhao, X.[Xin], Yu, Y.N.[Yi-Nan], Yang, M.[Ming], Huang, K.Q.[Kai-Qi],
SSAP: Single-Shot Instance Segmentation With Affinity Pyramid,
ICCV19(642-651)
IEEE DOI 2004
graph theory, image segmentation, learning (artificial intelligence), Acceleration BibRef

Xu, Y., Zhou, C., Yu, X., Xiao, B., Yang, Y.,
Pyramidal Multiple Instance Detection Network With Mask Guided Self-Correction for Weakly Supervised Object Detection,
IP(30), 2021, pp. 3029-3040.
IEEE DOI 2102
Proposals, Annotations, Object detection, Training, Image segmentation, Detectors, Task analysis, pyramidal network BibRef

Yu, J., Yao, J., Zhang, J., Yu, Z., Tao, D.,
SPRNet: Single-Pixel Reconstruction for One-Stage Instance Segmentation,
Cyber(51), No. 4, April 2021, pp. 1731-1742.
IEEE DOI 2103
Semantics, Detectors, Image segmentation, Object detection, Task analysis, Proposals, Image reconstruction, video analyze BibRef

Wu, Y.H., Liu, Y., Zhang, L., Gao, W., Cheng, M.M.,
Regularized Densely-Connected Pyramid Network for Salient Instance Segmentation,
IP(30), 2021, pp. 3897-3907.
IEEE DOI 2104
Feature extraction, Semantics, Image segmentation, Visualization, Task analysis, Object detection, Convolution, RoIAlign BibRef

Liu, Y.[Yun], Wu, Y.H.[Yu-Huan], Wen, P.S.[Pei-Song], Shi, Y.J.[Yu-Jun], Qiu, Y.[Yu], Cheng, M.M.[Ming-Ming],
Leveraging Instance-, Image- and Dataset-Level Information for Weakly Supervised Instance Segmentation,
PAMI(44), No. 3, March 2022, pp. 1415-1428.
IEEE DOI 2202
Semantics, Proposals, Image segmentation, Training, Probability distribution, Feature extraction, Noise measurement, multi-way cut BibRef

Zhu, L.C.[Lin-Chao], Fan, H.H.[He-He], Luo, Y.W.[Ya-Wei], Xu, M.L.[Ming-Liang], Yang, Y.[Yi],
Few-Shot Common-Object Reasoning Using Common-Centric Localization Network,
IP(30), 2021, pp. 4253-4262.
IEEE DOI 2104
Feature extraction, Object detection, Task analysis, Location awareness, Annotations, Cognition, Proposals, object detection BibRef

Wang, H.[Hui], Li, H.[Hao], Qian, W.L.[Wan-Li], Diao, W.H.[Wen-Hui], Zhao, L.J.[Liang-Jin], Zhang, J.H.[Jing-Hua], Zhang, D.B.[Dao-Bing],
Dynamic Pseudo-Label Generation for Weakly Supervised Object Detection in Remote Sensing Images,
RS(13), No. 8, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Fu, K.[Kun], Chang, Z.H.[Zhong-Han], Zhang, Y.[Yue], Sun, X.[Xian],
Point-Based Estimator for Arbitrary-Oriented Object Detection in Aerial Images,
GeoRS(59), No. 5, May 2021, pp. 4370-4387.
IEEE DOI 2104
Object detection, Detectors, Task analysis, Feature extraction, Predictive models, Object recognition, Quantization (signal), point-based estimator BibRef

Lu, J.Y.[Jun-Yan], Jia, H.G.[Hong-Guang], Li, T.[Tie], Li, Z.Q.[Zhu-Qiang], Ma, J.Y.[Jing-Yu], Zhu, R.F.[Rui-Fei],
An Instance Segmentation Based Framework for Large-Sized High-Resolution Remote Sensing Images Registration,
RS(13), No. 9, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Pang, J.M.[Jiang-Miao], Chen, K.[Kai], Li, Q.[Qi], Xu, Z.H.[Zhi-Hai], Feng, H.J.[Hua-Jun], Shi, J.P.[Jian-Ping], Ouyang, W.L.[Wan-Li], Lin, D.H.[Da-Hua],
Towards Balanced Learning for Instance Recognition,
IJCV(129), No. 5, May 2021, pp. 1376-1393.
Springer DOI 2105
BibRef

Sung, P.W.[Po-Wei], Yang, W.J.[Wei-Jong], Yang, J.F.[Jar-Ferr], Chan, D.Y.[Din-Yuan],
An interactive instance segmentation system with multi-resolution convolutional neural networks,
IET-CV(15), No. 2, 2021, pp. 99-109.
DOI Link 2106
BibRef

Liu, N.[Nian], Zhao, W.B.[Wang-Bo], Shao, L.[Ling], Han, J.W.[Jun-Wei],
SCG: Saliency and Contour Guided Salient Instance Segmentation,
IP(30), 2021, pp. 5862-5874.
IEEE DOI 2107
Task analysis, Saliency detection, Image segmentation, Head, Proposals, Feature extraction, Computational modeling, attention model BibRef

Gao, N.[Naiyu], Shan, Y.[Yanhu], Zhao, X.[Xin], Huang, K.Q.[Kai-Qi],
Learning Category- and Instance-Aware Pixel Embedding for Fast Panoptic Segmentation,
IP(30), 2021, pp. 6013-6023.
IEEE DOI 2107
Semantic and instance together. Image segmentation, Semantics, Predictive models, Task analysis, Pipelines, Image color analysis, Head, Panoptic segmentation, pixel embedding BibRef

Wu, Z.T.[Zi-Tong], Hou, B.[Biao], Ren, B.[Bo], Ren, Z.L.[Zhong-Le], Wang, S.[Shuang], Jiao, L.C.[Li-Cheng],
A Deep Detection Network Based on Interaction of Instance Segmentation and Object Detection for SAR Images,
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link 2107
BibRef

Zeng, X.F.[Xiang-Feng], Wei, S.J.[Shun-Jun], Wei, J.S.[Jin-Shan], Zhou, Z.C.[Zi-Chen], Shi, J.[Jun], Zhang, X.L.[Xiao-Ling], Fan, F.[Fan],
CPISNet: Delving into Consistent Proposals of Instance Segmentation Network for High-Resolution Aerial Images,
RS(13), No. 14, 2021, pp. xx-yy.
DOI Link 2107
BibRef

Yi, J.R.[Jing-Ru], Wu, P.X.[Peng-Xiang], Tang, H.[Hui], Liu, B.[Bo], Huang, Q.[Qiaoying], Qu, H.[Hui], Han, L.[Lianyi], Fan, W.[Wei], Hoeppner, D.J.[Daniel J.], Metaxas, D.N.[Dimitris N.],
Object-Guided Instance Segmentation With Auxiliary Feature Refinement for Biological Images,
MedImg(40), No. 9, September 2021, pp. 2403-2414.
IEEE DOI 2109
Image segmentation, Heating systems, Head, Feature extraction, Detectors, Object detection, Shape, Instance segmentation, medical image segmentation BibRef

Zhan, Y.[Yu], Zhao, W.L.[Wan-Lei],
Instance search via instance level segmentation and feature representation,
JVCIR(79), 2021, pp. 103253.
Elsevier DOI 2109
Instance search, Instance segmentation, CNN BibRef

Gominski, D.[Dimitri], Gouet-Brunet, V.[Valérie], Chen, L.M.[Li-Ming],
Connecting Images through Sources: Exploring Low-Data, Heterogeneous Instance Retrieval,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Hao, S.Y.[Sheng-Yu], Wang, G.[Gaoang], Gu, R.S.[Ren-Shu],
Weakly supervised instance segmentation using multi-prior fusion,
CVIU(211), 2021, pp. 103261.
Elsevier DOI 2110
Instance segmentation, Weakly supervised, Multi-priors, Bounding box annotations BibRef

Yang, F.[Feng], Yuan, X.Y.[Xiang-Yue], Ran, J.[Jie], Shu, W.Q.[Wen-Qiang], Zhao, Y.[Yue], Qin, A.[Anyong], Gao, C.Q.[Chen-Qiang],
Accurate Instance Segmentation for Remote Sensing Images via Adaptive and Dynamic Feature Learning,
RS(13), No. 23, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Wang, T.[Tao], Liew, J.H.[Jun Hao], Li, Y.[Yu], Chen, Y.P.[Yun-Peng], Feng, J.S.[Jia-Shi],
SODAR: Exploring Locally Aggregated Learning of Mask Representations for Instance Segmentation,
IP(31), 2022, pp. 839-851.
IEEE DOI 2201
Computer architecture, Microprocessors, Image segmentation, Convolution, Predictive models, Shape, Computational modeling, mask representation BibRef

Bolya, D.[Daniel], Zhou, C.[Chong], Xiao, F.[Fanyi], Lee, Y.J.[Yong Jae],
YOLACT++ Better Real-Time Instance Segmentation,
PAMI(44), No. 2, February 2022, pp. 1108-1121.
IEEE DOI 2201
BibRef
Earlier:
YOLACT: Real-Time Instance Segmentation,
ICCV19(9156-9165)
IEEE DOI 2004
Prototypes, Real-time systems, Image segmentation, Object detection, Detectors, Task analysis, Shape, real time. convolutional neural nets, learning (artificial intelligence) BibRef

Bolya, D.[Daniel], Foley, S.[Sean], Hays, J.[James], Hoffman, J.[Judy],
TIDE: A General Toolbox for Identifying Object Detection Errors,
ECCV20(III:558-573).
Springer DOI 2012
BibRef

Zhang, X.L.[Xiao-Liang], Li, H.L.[Hong-Liang], Meng, F.M.[Fan-Man], Song, Z.C.[Zi-Chen], Xu, L.F.[Lin-Feng],
Segmenting Beyond the Bounding Box for Instance Segmentation,
CirSysVideo(32), No. 2, February 2022, pp. 704-714.
IEEE DOI 2202
Object detection, Image segmentation, Semantics, Proposals, Detectors, Task analysis, Training, Instance segmentation, pixel embedding BibRef

Oksuz, K.[Kemal], Cam, B.C.[Baris Can], Akbas, E.[Emre], Kalkan, S.[Sinan],
Rank &Sort Loss for Object Detection and Instance Segmentation,
ICCV21(2989-2998)
IEEE DOI 2203
Training, Visualization, Pipelines, Detectors, Object detection, Multitasking, Loss measurement, BibRef

Wang, G.H.[Gai-Hua], Lin, J.H.[Jin-Heng], Zhai, Q.Y.[Qian-Yu], Cheng, L.[Lei], Dai, Y.Y.[Ying-Ying], Zhang, T.L.[Tian-Lun],
MAMask: Multi-feature aggregation instance segmentation with pyramid attention mechanism,
IET-IPR(16), No. 5, 2022, pp. 1341-1348.
DOI Link 2203
BibRef

Wang, G.H.[Gai-Hua], Zhai, Q.Y.[Qian-Yu], Lin, J.H.[Jin-Heng],
Multi-scale network for remote sensing segmentation,
IET-IPR(16), No. 6, 2022, pp. 1742-1751.
DOI Link 2204
BibRef

Gu, W.C.[Wen-Chao], Bai, S.[Shuang], Kong, L.X.[Ling-Xing],
A review on 2D instance segmentation based on deep neural networks,
IVC(120), 2022, pp. 104401.
Elsevier DOI 2204
Instance segmentation, Deep neural networks, Computer vision, Review BibRef

Chen, X.Y.[Xiao-Yu], Li, H.L.[Hong-Liang], Wu, Q.B.[Qing-Bo], Meng, F.M.[Fan-Man], Qiu, H.Q.[He-Qian],
Bal-R2CNN: High Quality Recurrent Object Detection With Balance Optimization,
MultMed(24), 2022, pp. 1558-1569.
IEEE DOI 2204
Proposals, Detectors, Location awareness, Optimization, Training, Task analysis, Object detection, Convolutional neural network, object recognition BibRef

Wang, Y.[Yan], Li, Y.[Yang], Guo, X.H.[Xiao-Hui], Jiao, L.C.[Li-Cheng], Liu, X.[Xu],
CDANet: Common-and-Differential Attention Network for Object Detection and Instance Segmentation,
PRL(158), 2022, pp. 48-54.
Elsevier DOI 2205
Object detection, Common-and-differential operations, Attention mechanism BibRef

Hu, J.F.[Jian-Fang], Sun, J.X.[Jiang-Xin], Lin, Z.H.[Zi-Hang], Lai, J.H.[Jian-Huang], Zeng, W.J.[Wen-Jun], Zheng, W.S.[Wei-Shi],
APANet: Auto-Path Aggregation for Future Instance Segmentation Prediction,
PAMI(44), No. 7, July 2022, pp. 3386-3403.
IEEE DOI 2206
Feature extraction, Image segmentation, Predictive models, Aggregates, Task analysis, Adaptation models, Hidden Markov models, auto-path aggregation BibRef

Yang, R.P.[Rui-Ping], Yu, J.[Jiguo], Yin, J.[Jian], Liu, K.[Kun], Xu, S.H.[Shao-Hua],
A dense R-CNN multi-target instance segmentation model and its application in medical image processing,
IET-IPR(16), No. 9, 2022, pp. 2495-2505.
DOI Link 2206
BibRef

Lv, K.F.[Ke-Feng], Zhang, Y.S.[Yong-Sheng], Yu, Y.[Ying], Wang, H.[Hanyun], Li, L.[Lei], Jiang, H.G.[Huai-Gang], Dai, C.G.[Chen-Guang],
Contour deformation network for instance segmentation,
PRL(159), 2022, pp. 213-219.
Elsevier DOI 2206
Instance segmentation, Contour deformation network, Graph convolutional network BibRef

Xie, E.[Enze], Wang, W.[Wenhai], Ding, M.Y.[Ming-Yu], Zhang, R.[Ruimao], Luo, P.[Ping],
PolarMask++: Enhanced Polar Representation for Single-Shot Instance Segmentation and Beyond,
PAMI(44), No. 9, September 2022, pp. 5385-5400.
IEEE DOI 2208
Pipelines, Image segmentation, Object detection, Feature extraction, Detectors, Tensors, Proposals, fully convolutional network BibRef

Xie, E., Sun, P., Song, X., Wang, W., Liu, X., Liang, D., Shen, C., Luo, P.,
PolarMask: Single Shot Instance Segmentation With Polar Representation,
CVPR20(12190-12199)
IEEE DOI 2008
Image segmentation, Task analysis, Training, Detectors, Complexity theory, Pipelines, Feature extraction BibRef

Zheng, Z.H.[Zhao-Hui], Wang, P.[Ping], Ren, D.W.[Dong-Wei], Liu, W.[Wei], Ye, R.G.[Rong-Guang], Hu, Q.H.[Qing-Hua], Zuo, W.M.[Wang-Meng],
Enhancing Geometric Factors in Model Learning and Inference for Object Detection and Instance Segmentation,
Cyber(52), No. 8, August 2022, pp. 8574-8586.
IEEE DOI 2208
Object detection, Training, Graphics processing units, Real-time systems, Detectors, Testing, Performance gain, object detection BibRef

Kim, N.[Namyup], Hwang, S.[Sehyun], Kwak, S.[Suha],
Learning to Detect Semantic Boundaries with Image-Level Class Labels,
IJCV(130), No. 9, September 2022, pp. 2131-2148.
Springer DOI 2208
BibRef

Kim, D.[Dongwon], Kim, N.[Namyup], Lan, C.L.[Cui-Ling], Kwak, S.[Suha],
Shatter and Gather: Learning Referring Image Segmentation with Text Supervision,
ICCV23(15501-15511)
IEEE DOI 2401
BibRef

Ahn, J.[Jiwoon], Cho, S.[Sunghyun], Kwak, S.[Suha],
Weakly Supervised Learning of Instance Segmentation With Inter-Pixel Relations,
CVPR19(2204-2213).
IEEE DOI 2002
BibRef
Earlier: A1, A3, Only:
Learning Pixel-Level Semantic Affinity with Image-Level Supervision for Weakly Supervised Semantic Segmentation,
CVPR18(4981-4990)
IEEE DOI 1812
Image segmentation, Semantics, Training, Shape, Visualization, Pipelines, Motion segmentation BibRef

Fan, H.[Hehe], Liu, P.[Ping], Xu, M.L.[Ming-Liang], Yang, Y.[Yi],
Unsupervised Visual Representation Learning via Dual-Level Progressive Similar Instance Selection,
Cyber(52), No. 9, September 2022, pp. 8851-8861.
IEEE DOI 2208
Visualization, Training, Task analysis, Reliability, Neural networks, Fans, Correlation, Deep learning, fine-grained categorization, unsupervised learning BibRef

Wu, J.L.[Jia-Lian], Song, L.C.[Liang-Chen], Zhang, Q.[Qian], Yang, M.[Ming], Yuan, J.S.[Jun-Song],
ForestDet: Large-Vocabulary Long-Tailed Object Detection and Instance Segmentation,
MultMed(24), 2022, pp. 3693-3705.
IEEE DOI 2208
Vegetation, Forestry, Noise measurement, Toy manufacturing industry, Proposals, long-tailed data distribution BibRef

Rossi, L.[Leonardo], Karimi, A.[Akbar], Prati, A.[Andrea],
Self-Balanced R-CNN for instance segmentation,
JVCIR(87), 2022, pp. 103595.
Elsevier DOI 2208
Object detection, Instance segmentation, Imbalance in R-CNN networks, Two-stage deep learning architectures BibRef

Ahmed, I.[Imran], Ahmad, M.[Misbah], Chehri, A.[Abdellah], Hassan, M.M.[Mohammad Mehedi], Jeon, G.G.[Gwang-Gil],
IoT Enabled Deep Learning Based Framework for Multiple Object Detection in Remote Sensing Images,
RS(14), No. 16, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Yin, C.X.[Cheng-Xiang], Tang, J.[Jian], Yuan, T.T.[Tong-Tong], Xu, Z.Y.[Zhi-Yuan], Wang, Y.Z.[Yan-Zhi],
Bridging the Gap Between Semantic Segmentation and Instance Segmentation,
MultMed(24), 2022, pp. 4183-4196.
IEEE DOI 2209
Semantics, Image segmentation, Real-time systems, Training, Task analysis, Neurons, Head, Semantic segmentation, sem2Ins BibRef

Zhao, B.[Bowen], Chen, C.[Chen], Xiao, X.[Xi], Xia, S.T.[Shu-Tao],
Towards a category-extended object detector with limited data,
PR(132), 2022, pp. 108943.
Elsevier DOI 2209
Object detector, Category-extended, Limited data, Multi-dataset BibRef

Guo, X.L.[Xiao-Long], Lan, X.S.[Xiao-Song], Wang, K.[Kunfeng], Li, S.[Shuxiao],
Contour loss for instance segmentation via k-step distance transformation image,
IET-CV(16), No. 8, 2022, pp. 683-693.
DOI Link 2210
BibRef

Wang, X.L.[Xin-Long], Zhang, R.F.[Ru-Feng], Shen, C.H.[Chun-Hua], Kong, T.[Tao], Li, L.[Lei],
SOLO: A Simple Framework for Instance Segmentation,
PAMI(44), No. 11, November 2022, pp. 8587-8601.
IEEE DOI 2210
Image segmentation, Semantics, Object detection, Task analysis, Kernel, Training, Standards, Instance segmentation, object detection, segmenting objects by locations BibRef

Zhang, Q.L.[Qing-Long], Yang, Y.B.[Yu-Bin],
A boundary-preserving conditional convolution network for instance segmentation,
PRL(163), 2022, pp. 1-9.
Elsevier DOI 2212
Instance segmentation, Boundary-preserving, Conditional convolution, Post-processing mechanism BibRef

Zhao, X.Q.[Xin-Qiao], Xiao, J.[Jimin], Zhang, B.F.[Bing-Feng], Zhang, Q.[Quan], Waleed, A.N.[Al-Nuaimy],
Weight-Guided Loss for Long-Tailed Object Detection and Instance Segmentation,
SP:IC(110), 2023, pp. 116874.
Elsevier DOI 2212
Long-tail, Object detection, Instance segmentation BibRef

Ye, W.J.[Wu-Jian], Liu, C.J.[Chao-Jie], Chen, Y.H.[Yue-Hai], Liu, Y.J.[Yi-Jun], Liu, C.M.[Chen-Ming], Zhou, H.H.[Hui-Hui],
Multi-style transfer and fusion of image's regions based on attention mechanism and instance segmentation,
SP:IC(110), 2023, pp. 116871.
Elsevier DOI 2212
Multi-style transfer, Attention mechanism, Regional stylization, Instance segmentation, Poisson fusion BibRef

Zhang, Z.Y.[Zhong-Yan], Wang, L.[Lei], Wang, Y.[Yang], Zhou, L.P.[Lu-Ping], Zhang, J.[Jianjia], Chen, F.[Fang],
Dataset-Driven Unsupervised Object Discovery for Region-Based Instance Image Retrieval,
PAMI(45), No. 1, January 2023, pp. 247-263.
IEEE DOI 2212
Detectors, Image retrieval, Feature extraction, Object detection, Task analysis, Reliability, Training, Instance image retrieval, unsupervised learning BibRef

Yang, L.R.[Long-Rong], Li, H.L.[Hong-Liang], Meng, F.M.[Fan-Man], Wu, Q.B.[Qing-Bo], Ngan, K.N.[King Ngi],
Task-Specific Loss for Robust Instance Segmentation With Noisy Class Labels,
CirSysVideo(33), No. 1, January 2023, pp. 213-227.
IEEE DOI 2301
Noise measurement, Task analysis, Image segmentation, Entropy, Proposals, Semantics, Annotations, Noisy class labels, self-supervised learning BibRef

Yang, L.R.[Long-Rong], Meng, F.M.[Fan-Man], Li, H.L.[Hong-Liang], Wu, Q.B.[Qing-Bo], Cheng, Q.S.[Qi-Shang],
Learning with Noisy Class Labels for Instance Segmentation,
ECCV20(XIV:38-53).
Springer DOI 2011
BibRef

Zhang, J.B.[Jia-Bin], Su, H.[Hu], He, Y.H.[Yong-Hao], Zou, W.[Wei],
Weakly Supervised Instance Segmentation via Category-aware Centerness Learning with Localization Supervision,
PR(136), 2023, pp. 109165.
Elsevier DOI 2301
Weakly supervised learning, Instance segmentation, Centerness, Coarse localization annotation BibRef

Cao, J.[Jiale], Pang, Y.W.[Yan-Wei], Anwer, R.M.[Rao Muhammad], Cholakkal, H.[Hisham], Khan, F.S.[Fahad Shahbaz], Shao, L.[Ling],
SipMaskv2: Enhanced Fast Image and Video Instance Segmentation,
PAMI(45), No. 3, March 2023, pp. 3798-3812.
IEEE DOI 2302
BibRef
Earlier: A1, A3, A4, A5, A2, A6:
Sipmask: Spatial Information Preservation for Fast Image and Video Instance Segmentation,
ECCV20(XIV:1-18).
Springer DOI 2011
Image segmentation, Training, Real-time systems, Proposals, Feature extraction, Object detection, Task analysis, spatial information preservation BibRef

Zhang, K.[Ke], Yuan, C.[Chun], Zhu, Y.M.[Yi-Ming], Jiang, Y.[Yong], Luo, L.[Lishu],
Weakly Supervised Instance Segmentation by Exploring Entire Object Regions,
MultMed(25), 2023, pp. 352-363.
IEEE DOI 2302
Image segmentation, Semantics, Task analysis, Streaming media, Location awareness, Saliency detection, Training, integration module BibRef

Zhou, J.H.[Jia-Huan], Su, B.[Bing], Wu, Y.[Ying],
Discriminative Self-Paced Group-Metric Adaptation for Online Visual Identification,
PAMI(45), No. 4, April 2023, pp. 4368-4383.
IEEE DOI 2303
Visualization, Testing, Adaptation models, Measurement, Training, Data models, Feature extraction, Learning from sharing, self-paced learning BibRef

Koporec, G.[Gregor], Perš, J.[Janez],
Human-centered deep compositional model for handling occlusions,
PR(138), 2023, pp. 109397.
Elsevier DOI 2303
Convolutional neural networks, Hierarchical compositonal model, Instance segmentation, Domain knowledge BibRef

Guan, L.[Licong], Yuan, X.[Xue],
Instance Segmentation Model Evaluation and Rapid Deployment for Autonomous Driving Using Domain Differences,
ITS(24), No. 4, April 2023, pp. 4050-4059.
IEEE DOI 2304
Autonomous vehicles, Image segmentation, Adaptation models, Predictive models, Data models, Training, Task analysis, domain difference BibRef

Chen, W.[Wei], Liu, Y.[Yu], Wang, W.P.[Wei-Ping], Bakker, E.M.[Erwin M.], Georgiou, T.[Theodoros], Fieguth, P.[Paul], Liu, L.[Li], Lew, M.S.[Michael S.],
Deep Learning for Instance Retrieval: A Survey,
PAMI(45), No. 6, June 2023, pp. 7270-7292.
IEEE DOI 2305
Feature extraction, Image retrieval, Deep learning, Task analysis, Analytical models, Convolutional neural networks, Visualization, literature survey BibRef

Qi, L.[Lu], Kuen, J.[Jason], Wang, Y.[Yi], Gu, J.X.[Jiu-Xiang], Zhao, H.S.[Heng-Shuang], Torr, P.H.S.[Philip H.S.], Lin, Z.[Zhe], Jia, J.Y.[Jia-Ya],
Open World Entity Segmentation,
PAMI(45), No. 7, July 2023, pp. 8743-8756.
IEEE DOI 2306
Image segmentation, Task analysis, Training, Object detection, Visualization, Standards, Semantics, Image segmentation, cross-dataset BibRef

Huynh, D.[Dat], Kuen, J.[Jason], Lin, Z.[Zhe], Gu, J.X.[Jiu-Xiang], Elhamifar, E.[Ehsan],
Open-Vocabulary Instance Segmentation via Robust Cross-Modal Pseudo-Labeling,
CVPR22(7010-7021)
IEEE DOI 2210
Training, Image segmentation, Visualization, Annotations, Semantics, Pattern recognition, Transfer/low-shot/long-tail learning, grouping and shape analysis BibRef

Pei, J.L.[Jia-Lun], Cheng, T.Y.[Tian-Yang], Tang, H.[He], Chen, C.B.[Chuan-Bo],
Transformer-Based Efficient Salient Instance Segmentation Networks With Orientative Query,
MultMed(25), 2023, pp. 1964-1978.
IEEE DOI 2306
Transformers, Task analysis, Object detection, Image segmentation, Decoding, Visualization, Training, Salient instance segmentation, attention model BibRef

Zhang, X.Q.[Xiang-Qing], Feng, Y.[Yan], Zhang, S.[Shun], Wang, N.[Nan], Mei, S.H.[Shao-Hui], He, M.Y.[Ming-Yi],
Semi-Supervised Person Detection in Aerial Images with Instance Segmentation and Maximum Mean Discrepancy Distance,
RS(15), No. 11, 2023, pp. 2928.
DOI Link 2306
BibRef

Ke, L.[Lei], Tai, Y.W.[Yu-Wing], Tang, C.K.[Chi-Keung],
Occlusion-Aware Instance Segmentation Via BiLayer Network Architectures,
PAMI(45), No. 8, August 2023, pp. 10197-10211.
IEEE DOI 2307
BibRef
Earlier:
Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers,
CVPR21(4018-4027)
IEEE DOI 2111
Transformers, Image segmentation, Decoding, Magnetic heads, Head, Convolutional neural networks, Task analysis, BCNet, occlusion-aware video instance segmen- tation. Convolutional codes, Computational modeling, Detectors, Performance gain BibRef

Li, D.W.[Da-Wei], Li, W.B.[Wen-Bo], Jin, H.X.[Hong-Xia],
Foreground-specialized Model Imitation for Instance Segmentation,
ACCV22(VII:398-413).
Springer DOI 2307
BibRef

Chen, L.W.[Lin-Wei], Fu, Y.[Ying], Wei, K.X.[Kai-Xuan], Zheng, D.Z.[De-Zhi], Heide, F.[Felix],
Instance Segmentation in the Dark,
IJCV(131), No. 8, August 2023, pp. 2198-2218.
Springer DOI 2307
BibRef

Wang, Y.Q.[Yu-Qi], Chen, Y.T.[Yun-Tao], Zhang, Z.X.[Zhao-Xiang],
Object Affinity Learning: Towards Annotation-Free Instance Segmentation,
PAMI(45), No. 11, November 2023, pp. 13959-13973.
IEEE DOI 2310
BibRef

Cheng, T.H.[Tian-Heng], Wang, X.G.[Xing-Gang], Chen, S.Y.[Shao-Yu], Zhang, W.Q.[Wen-Qiang], Zhang, Q.[Qian], Huang, C.[Chang], Zhang, Z.X.[Zhao-Xiang], Liu, W.Y.[Wen-Yu],
Sparse Instance Activation for Real-Time Instance Segmentation,
CVPR22(4423-4432)
IEEE DOI 2210
Convolutional codes, Aggregates, Object detection, Benchmark testing, Real-time systems, Pattern recognition, retrieval BibRef

Chu, K.C.[Kuan-Chao], Nakayama, H.[Hideki],
Two-Path Object Knowledge Injection for Detecting Novel Objects with Single-Stage Dense Detector,
IEICE(E106-D), No. 11, November 2023, pp. 1868-1880.
WWW Link. 2311
BibRef

Zhang, Y.[Yue], Liang, C.[Chao], Jiang, L.X.[Long-Xiang],
Confidence-Aware Active Feedback for Interactive Instance Search,
MultMed(25), 2023, pp. 7173-7184.
IEEE DOI Code:
WWW Link. 2311
BibRef

Song, M.S.[Min-Soo], Um, G.M.[Gi-Mun], Lee, H.K.[Hee Kyung], Seo, J.[Jeongil], Kim, W.J.[Won-Jun],
Dynamic Residual Filtering With Laplacian Pyramid for Instance Segmentation,
MultMed(25), 2023, pp. 6892-6903.
IEEE DOI Code:
WWW Link. 2311
BibRef

Yang, L.[Longrong], Li, H.L.[Hong-Liang], Wu, Q.B.[Qing-Bo], Meng, F.M.[Fan-Man], Qiu, H.Q.[He-Qian], Xu, L.F.[Lin-Feng],
Bias-Correction Feature Learner for Semi-Supervised Instance Segmentation,
MultMed(25), 2023, pp. 5852-5863.
IEEE DOI 2311
BibRef

Yelleni, S.H.[Sai Harsha], Kumari, D.[Deepshikha], Srijith, P.K., Mohan, C.K.[C. Krishna],
Monte Carlo DropBlock for modeling uncertainty in object detection,
PR(146), 2024, pp. 110003.
Elsevier DOI 2311
Monte Carlo method, DropBlock, Object detection, Bayesian deep learning, Uncertainty estimation, Instance segmentation BibRef

Ye-Bin, M.[Moon], Choi, D.[Dongmin], Kwon, Y.J.[Yong-Jin], Kim, J.[Junsik], Oh, T.H.[Tae-Hyun],
ENInst: Enhancing weakly-supervised low-shot instance segmentation,
PR(145), 2024, pp. 109888.
Elsevier DOI 2311
Low-shot learning, Weakly-supervised learning, Instance segmentation, Sub-task analysis, Enhancement methods BibRef

Li, Y.J.[Yu-Jie], Cai, J.[Jintong], Zhou, Q.[Quan], Lu, H.M.[Hui-Min],
Joint Semantic-Instance Segmentation Method for Intelligent Transportation System,
ITS(24), No. 12, December 2023, pp. 15540-15547.
IEEE DOI 2312
BibRef

Tang, X.Q.[Xiao-Qin], Lv, L.P.[Ling-Peng], Javanmardi, S.[Shima], Wang, Y.F.[Yun-Feng], Fan, J.[Jingchuan], Verbeek, F.J.[Fons J.], Xiao, G.Q.[Guo-Qiang],
Image Synthesis and Modified BlendMask Instance Segmentation for Automated Nanoparticle Phenotyping,
MedImg(42), No. 12, December 2023, pp. 3665-3677.
IEEE DOI 2312
BibRef

Zhu, L.J.[Liang-Jun], Peng, L.[Li], Ding, S.C.[Shu-Chen], Liu, Z.R.[Zhong-Ren],
An encoder-decoder framework with dynamic convolution for weakly supervised instance segmentation,
IET-CV(17), No. 8, 2023, pp. 883-894.
DOI Link 2312
image segmentation, object detection BibRef

Kachole, S.[Sanket], Huang, X.Q.[Xiao-Qian], Naeini, F.B.[Fariborz Baghaei], Muthusamy, R.[Rajkumar], Makris, D.[Dimitrios], Zweiri, Y.[Yahya],
Bimodal SegNet: Fused instance segmentation using events and RGB frames,
PR(149), 2024, pp. 110215.
Elsevier DOI Code:
WWW Link. 2403
Robotics, Grasping, Event vision, Deep learning, Cross attention BibRef

Li, B.[Bo], Zhu, J.S.[Jian-Sheng], Dai, L.L.[Lin-Lin], Jing, H.[Hui], Huang, Z.Z.[Zhi-Zheng],
The impact of introducing textual semantics on item instance retrieval with highly similar appearance: An empirical study,
IVC(143), 2024, pp. 104925.
Elsevier DOI 2403
Image instance retrieval, Multi-modal fusion, Deep-learning, Neural networks, Cross-modal embedding BibRef

Ji, Z.L.[Zong-Liang], Veksler, O.[Olga],
Regularized Loss With Hyperparameter Estimation for Weakly Supervised Single Class Segmentation,
PAMI(46), No. 5, May 2024, pp. 3923-3937.
IEEE DOI 2404
BibRef
Earlier: A2, Only:
Regularized Loss for Weakly Supervised Single Class Semantic Segmentation,
ECCV20(XXIX: 348-365).
Springer DOI 2010
Training, Cams, Conditional random fields, Task analysis, Semantic segmentation, Annotations, Annealing, Co-segmentation, weak supervision BibRef

Hu, J.[Jie], Lu, Y.[Yao], Zhang, S.[Shengchuan], Cao, L.J.[Liu-Juan],
ISTR: Mask-Embedding-Based Instance Segmentation Transformer,
IP(33), 2024, pp. 2895-2907.
IEEE DOI Code:
WWW Link. 2405
Transformers, Instance segmentation, Pipelines, Decoding, Principal component analysis, Discrete cosine transforms, Tuners, mutual information maximization BibRef

Zhao, Y.[Yaochi], Chen, S.[Sen], Liu, S.G.[Shi-Guang], Hu, Z.[Zhuhua], Xia, J.W.[Jing-Wen],
Hierarchical Equalization Loss for Long-Tailed Instance Segmentation,
MultMed(26), 2024, pp. 6943-6955.
IEEE DOI 2405
Instance segmentation, Tail, Training, Object detection, Deep learning, Task analysis, Residual neural networks BibRef

Huang, Z.X.[Zu-Xian], Pan, D.S.[Dong-Sheng], Wu, G.S.[Gang-Shan],
Weakly supervised instance segmentation via peak mining and filtering,
IET-IPR(18), No. 6, 2024, pp. 1565-1578.
DOI Link 2405
image segmentation BibRef


Ao, J.Y.[Jia-Yang], Ke, Q.H.[Qiu-Hong], Ehinger, K.A.[Krista A.],
Amodal Intra-class Instance Segmentation: Synthetic Datasets and Benchmark,
WACV24(280-289)
IEEE DOI 2404
Instance segmentation, Training, Annotations, Grasping, Benchmark testing, Task analysis, Algorithms, Datasets and evaluations BibRef

Berrada, T.[Tariq], Couprie, C.[Camille], Alahari, K.[Karteek], Verbeek, J.[Jakob],
Guided Distillation for Semi-Supervised Instance Segmentation,
WACV24(464-472)
IEEE DOI 2404
Instance segmentation, Training, Training data, Computer architecture, Object detection, Transformers, and algorithms BibRef

Hossain, M.R.I.[Mir Rayat Imtiaz], Sigal, L.[Leonid], Little, J.J.[James J.],
Framework-agnostic Semantically-aware Global Reasoning for Segmentation,
WACV24(988-998)
IEEE DOI 2404
Measurement, Instance segmentation, Head, Semantics, Object detection, Transformers, Algorithms, and algorithms BibRef

Siddiqui, Q.M.K.[Qasim M. K.], Starke, S.[Sebastian], Steinbach, P.[Peter],
Uncertainty Estimation in Instance Segmentation with Star-convex Shapes,
WACV24(1413-1422)
IEEE DOI 2404
Instance segmentation, Uncertainty, Monte Carlo methods, Shape, Decision making, Estimation, Predictive models, Algorithms, Visualization BibRef

Liu, Y.F.[Yi-Fei], Gehrig, M.[Mathias], Messikommer, N.[Nico], Cannici, M.[Marco], Scaramuzza, D.[Davide],
Revisiting Token Pruning for Object Detection and Instance Segmentation,
WACV24(2646-2656)
IEEE DOI Code:
WWW Link. 2404
Instance segmentation, Codes, Object detection, Transformers, Computational efficiency, Task analysis, Algorithms, Image recognition and understanding BibRef

Gorlo, N.[Nicolas], Blomqvist, K.[Kenneth], Milano, F.[Francesco], Siegwart, R.[Roland],
ISAR: A Benchmark for Single- and Few-Shot Object Instance Segmentation and Re-Identification,
WACV24(4372-4384)
IEEE DOI 2404
Instance segmentation, Training, Annotations, Tracking, Video sequences, Object segmentation, Algorithms, Video recognition and understanding BibRef

Valvano, G.[Gabriele], Agostino, A.[Antonino], de Magistris, G.[Giovanni], Graziano, A.[Antonino], Veneri, G.[Giacomo],
Controllable Image Synthesis of Industrial Data using Stable Diffusion,
WACV24(5342-5351)
IEEE DOI 2404
Training, Measurement, Instance segmentation, Industries, Adaptation models, Image synthesis, Production, Algorithms, Commercial / retail BibRef

Ren, S.[Simiao], Luzi, F.[Francesco], Lahrichi, S.[Saad], Kassaw, K.[Kaleb], Collins, L.M.[Leslie M.], Bradbury, K.[Kyle], Malof, J.M.[Jordan M.],
Segment anything, from space?,
WACV24(8340-8350)
IEEE DOI 2404
Instance segmentation, Image segmentation, Systematics, Annotations, Target recognition, Roads, Benchmark testing, Image recognition and understanding BibRef

Zielinski, P.[Piotr], Kajdanowicz, T.[Tomasz],
RDIR: Capturing Temporally-Invariant Representations of Multiple Objects in Videos,
Pretrain24(588-597)
IEEE DOI 2404
Instance segmentation, Sensitivity, Computational modeling, Neural networks, Information sharing, Object detection, Robustness BibRef

Yang, R.[Rui], Song, L.[Lin], Ge, Y.X.[Yi-Xiao], Li, X.[Xiu],
BoxSnake: Polygonal Instance Segmentation with Box Supervision,
ICCV23(766-776)
IEEE DOI Code:
WWW Link. 2401
BibRef

Lian, S.J.[Shi-Jie], Li, H.[Hua], Cong, R.[Runmin], Li, S.[Suqi], Zhang, W.[Wei], Kwong, S.[Sam],
WaterMask: Instance Segmentation for Underwater Imagery,
ICCV23(1305-1315)
IEEE DOI Code:
WWW Link. 2401
BibRef

Wu, J.N.[Jian-Nan], Jiang, Y.[Yi], Yan, B.[Bin], Lu, H.C.[Hu-Chuan], Yuan, Z.H.[Ze-Huan], Luo, P.[Ping],
Exploring Transformers for Open-world Instance Segmentation,
ICCV23(6588-6598)
IEEE DOI 2401
BibRef

Hu, J.[Jie], Chen, C.[Chen], Cao, L.J.[Liu-Juan], Zhang, S.C.[Sheng-Chuan], Shu, A.[Annan], Jiang, G.N.[Guan-Nan], Ji, R.R.[Rong-Rong],
Pseudo-Label Alignment for Semi-Supervised Instance Segmentation,
ICCV23(16291-16301)
IEEE DOI Code:
WWW Link. 2401
BibRef

Liu, X.Y.[Xiao-Yu], Huang, W.[Wei], Xiong, Z.W.[Zhi-Wei], Zhou, S.L.[Sheng-Long], Zhang, Y.[Yueyi], Chen, X.J.[Xue-Jin], Zha, Z.J.[Zheng-Jun], Wu, F.[Feng],
Learning Cross-Representation Affinity Consistency for Sparsely Supervised Biomedical Instance Segmentation,
ICCV23(21050-21060)
IEEE DOI Code:
WWW Link. 2401
BibRef

Wu, J.[Jianzong], Li, X.T.[Xiang-Tai], Ding, H.H.[Heng-Hui], Li, X.[Xia], Cheng, G.L.[Guang-Liang], Tong, Y.H.[Yun-Hai], Loy, C.C.[Chen Change],
Betrayed by Captions: Joint Caption Grounding and Generation for Open Vocabulary Instance Segmentation,
ICCV23(21881-21891)
IEEE DOI 2401
BibRef

Ülger, O.[Osman], Wang, Y.[Yu], Galama, Y.[Ysbrand], Karaoglu, S.[Sezer], Gevers, T.[Theo], Oswald, M.R.[Martin R.],
Relational Prior Knowledge Graphs for Detection and Instance Segmentation,
SG2RL23(53-61)
IEEE DOI 2401
BibRef

Rustia, D.J.A.[Dan Jeric Arcega], Jansen, G.A.[Guido Alexander], Hageraats, S.[Selwin], Peller, J.[Joseph], van de Zedde, R.[Rick], Marchennay, C.[Cécile], Sangster, W.[Wim], Blokker, G.[Gosia],
Rapid tomato DUS trait analysis using an optimized mobile-based coarse-to-fine instance segmentation algorithm,
CVPPA23(634-642)
IEEE DOI 2401
BibRef

Rumberger, J.L.[Josef Lorenz], Franzen, J.[Jannik], Hirsch, P.[Peter], Albrecht, J.P.[Jan-Philipp], Kainmueller, D.[Dagmar],
ACTIS: Improving data efficiency by leveraging semi-supervised Augmentation Consistency Training for Instance Segmentation,
BioIm23(3792-3801)
IEEE DOI Code:
WWW Link. 2401
BibRef

Chen, Q.[Qi], Huang, W.[Wei], Liu, X.Y.[Xiao-Yu], Li, J.C.[Jia-Cheng], Xiong, Z.W.[Zhi-Wei],
PCTrans: Position-Guided Transformer with Query Contrast for Biological Instance Segmentation,
BioIm23(3905-3914)
IEEE DOI Code:
WWW Link. 2401
BibRef

Chen, L.[Long], Wu, Y.[Yuli], Stegmaier, J.[Johannes], Merhof, D.[Dorit],
SortedAP: Rethinking evaluation metrics for instance segmentation,
BioIm23(3925-3931)
IEEE DOI Code:
WWW Link. 2401
BibRef

Hsieh, Y.H.[Yu-Hsing], Chen, G.S.[Guan-Sheng], Cai, S.X.[Shun-Xian], Wei, T.Y.[Ting-Yun], Yang, H.F.[Huei-Fang], Chen, C.S.[Chu-Song],
Class-incremental Continual Learning for Instance Segmentation with Image-level Weak Supervision,
ICCV23(1250-1261)
IEEE DOI 2401
BibRef

Kilis, N.[Nikolaos], Tsipouridis, G.[Grigorios], Karakostas, I.[Iason], Dimitriou, N.[Nikolaos], Tzovaras, D.[Dimitrios],
Augmentation Based on Artificial Occlusions for Resilient Instance Segmentation,
CIAP23(II:37-48).
Springer DOI 2312
BibRef

Song, J.[Jie], Cai, Z.[Ziyun], Song, Y.R.[Yu-Rong], Jiang, G.P.[Guo-Ping], Lian, Z.C.[Zhi-Chao], Xiao, L.[Liang],
Learnable Snake R-CNN for Instance-Level Biomedical Image Segmentation,
ICIP23(2920-2924)
IEEE DOI 2312
BibRef

Jiang, S.H.[Shang-Hang], Zhao, S.C.[Shi-Chao], Wu, M.[Meng], Zhang, L.[Le], Zhou, F.[Feng],
Overlap Loss: Rethinking Weakly Supervised Instance Segmentation in Crowded Scenes,
ICIP23(2905-2909)
IEEE DOI Code:
WWW Link. 2312
BibRef

Firoze, A.[Adnan], Wingren, C.[Cameron], Yeh, R.A.[Raymond A.], Benes, B.[Bedrich], Aliaga, D.[Daniel],
Tree Instance Segmentation with Temporal Contour Graph,
CVPR23(2193-2202)
IEEE DOI 2309
BibRef

Jena, R.[Rohit], Zhornyak, L.[Lukas], Doiphode, N.[Nehal], Chaudhari, P.[Pratik], Buch, V.[Vivek], Gee, J.[James], Shi, J.B.[Jian-Bo],
Beyond mAP: Towards Better Evaluation of Instance Segmentation,
CVPR23(11309-11318)
IEEE DOI 2309
BibRef

Li, R.H.[Rui-Huang], He, C.H.[Chen-Hang], Li, S.[Shuai], Zhang, Y.[Yabin], Zhang, L.[Lei],
DynaMask: Dynamic Mask Selection for Instance Segmentation,
CVPR23(11279-11288)
IEEE DOI 2309
BibRef

Shin, G.[Gyungin], Xie, W.[Weidi], Albanie, S.[Samuel],
NamedMask: Distilling Segmenters from Complementary Foundation Models,
L3D-IVU23(4961-4970)
IEEE DOI 2309
BibRef

Shin, G.[Gyungin], Albanie, S.[Samuel], Xie, W.[Weidi],
Zero-shot Unsupervised Transfer Instance Segmentation,
L3D-IVU23(4848-4858)
IEEE DOI 2309
BibRef

Su, J.M.[Jin-Ming], Yin, R.[Ruihong], Chen, X.Y.[Xing-Yue], Luo, J.F.[Jun-Feng],
Perceive, Excavate and Purify: A Novel Object Mining Framework for Instance Segmentation,
PVUW23(3581-3590)
IEEE DOI 2309
BibRef

Yoon, J.[Jihun], Choi, M.K.[Min-Kook],
Exploring Video Frame Redundancies for Efficient Data Sampling and Annotation in Instance Segmentation,
VDU23(3308-3317)
IEEE DOI 2309
BibRef

He, J.J.[Jun-Jie], Li, P.Y.[Peng-Yu], Geng, Y.F.[Yi-Feng], Xie, X.[Xuansong],
FastInst: A Simple Query-Based Model for Real-Time Instance Segmentation,
CVPR23(23663-23672)
IEEE DOI 2309
BibRef

Vibashan, V.S., Yu, N.[Ning], Xing, C.[Chen], Qin, C.[Can], Gao, M.F.[Ming-Fei], Niebles, J.C.[Juan Carlos], Patel, V.M.[Vishal M.], Xu, R.[Ran],
Mask-Free OVIS: Open-Vocabulary Instance Segmentation without Manual Mask Annotations,
CVPR23(23539-23549)
IEEE DOI 2309
BibRef

Liao, M.X.[Ming-Xiang], Guo, Z.[Zonghao], Wang, Y.Z.[Yu-Ze], Yuan, P.[Peng], Feng, B.[Bailan], Wan, F.[Fang],
AttentionShift: Iteratively Estimated Part-Based Attention Map for Pointly Supervised Instance Segmentation,
CVPR23(19519-19528)
IEEE DOI 2309
BibRef

He, S.T.[Shu-Ting], Ding, H.H.[Heng-Hui], Jiang, W.[Wei],
Semantic-Promoted Debiasing and Background Disambiguation for Zero-Shot Instance Segmentation,
CVPR23(19498-19507)
IEEE DOI 2309
BibRef

Ishtiak, T.[Taoseef], En, Q.[Qing], Guo, Y.H.[Yu-Hong],
Exemplar-FreeSOLO: Enhancing Unsupervised Instance Segmentation with Exemplars,
CVPR23(15424-15433)
IEEE DOI 2309
BibRef

Yan, B.[Bin], Jiang, Y.[Yi], Wu, J.N.[Jian-Nan], Wang, D.[Dong], Luo, P.[Ping], Yuan, Z.H.[Ze-Huan], Lu, H.C.[Hu-Chuan],
Universal Instance Perception as Object Discovery and Retrieval,
CVPR23(15325-15336)
IEEE DOI 2309
BibRef

Li, R.H.[Rui-Huang], He, C.[Chenhang], Zhang, Y.[Yabin], Li, S.[Shuai], Chen, L.[Liyi], Zhang, L.[Lei],
SIM: Semantic-aware Instance Mask Generation for Box-Supervised Instance Segmentation,
CVPR23(7193-7203)
IEEE DOI 2309
BibRef

Cho, J.H.[Jang Hyun], Krähenbühl, P.[Philipp], Ramanathan, V.[Vignesh],
PartDistillation: Learning Parts from Instance Segmentation,
CVPR23(7152-7161)
IEEE DOI 2309
BibRef

Wang, X.D.[Xu-Dong], Girdhar, R.[Rohit], Yu, S.X.[Stella X.], Misra, I.[Ishan],
Cut and Learn for Unsupervised Object Detection and Instance Segmentation,
CVPR23(3124-3134)
IEEE DOI 2309
BibRef

Li, H.[Hao], Zhang, D.W.[Ding-Wen], Liu, N.[Nian], Cheng, L.[Lechao], Dai, Y.[Yalun], Zhang, C.[Chao], Wang, X.G.[Xing-Gang], Han, J.W.[Jun-Wei],
Boosting Low-Data Instance Segmentation by Unsupervised Pre-training with Saliency Prompt,
CVPR23(15485-15494)
IEEE DOI 2309
BibRef

Zhao, J.[Jing], Wu, S.J.[Sheng-Jian], Sun, L.[Li], Li, Q.L.[Qing-Li],
IOU-enhanced Attention for End-to-end Task Specific Object Detection,
ACCV22(V:124-141).
Springer DOI 2307
BibRef

Tang, L.[Linghua], Hui, L.[Le], Xie, J.[Jin],
Learning Inter-superpoint Affinity for Weakly Supervised 3d Instance Segmentation,
ACCV22(I:176-192).
Springer DOI 2307
BibRef

Hu, Z.Q.[Zhi-Qi], Brilakis, I.[Ioannis],
PRISEG: IFC-supported Primitive Instance Geometry Segmentation with Unsupervised Clustering,
CVCivil22(196-211).
Springer DOI 2304
BibRef

Kara, S.[Sandra], Ammar, H.[Hejer], Chabot, F.[Florian], Pham, Q.C.[Quoc-Cuong],
Image Segmentation-based Unsupervised Multiple Objects Discovery,
WACV23(3276-3285)
IEEE DOI 2302
Learning systems, Image segmentation, Annotations, Semantics, Object detection, Information filters BibRef

Listed, N.A.[No Author],
Unsupervised Multi-Object Segmentation Using Attention and Soft-Argmax,
WACV23(3266-3275)
IEEE DOI 2302
Algorithms: Image recognition and understanding, object detection BibRef

Hsieh, H.Y.[He-Yen], Chen, D.J.[Ding-Jie], Chang, C.W.[Cheng-Wei], Liu, T.L.[Tyng-Luh],
Aggregating Bilateral Attention for Few-Shot Instance Localization,
WACV23(6314-6323)
IEEE DOI 2302
Location awareness, Filtering, Computational modeling, Neural networks, Focusing, Context awareness, Object detection BibRef

Boyadzhiev, T.[Teodor], Ivanova, K.[Krassimira],
Instance Segmentation with BoundaryNet,
IWCIA22(260-269).
Springer DOI 2301
BibRef

Lee, S.I.[Seung Il], Kim, H.[Hyun],
GaussianMask: Uncertainty-aware Instance Segmentation based on Gaussian Modeling,
ICPR22(3851-3857)
IEEE DOI 2212
Location awareness, Adaptation models, Uncertainty, Computational modeling, Predictive models BibRef

Uchinoura, S.[Shinji], Kurita, T.[Takio],
Graph Laplacian Regularization based on the Differences of Neighboring Pixels for Conditional Convolutions for Instance Segmentation,
ICPR22(3611-3617)
IEEE DOI 2212
Laplace equations, Computational modeling, Task analysis, Videos, Context modeling BibRef

Sayez, N.[Niels], Vleeschouwer, C.D.[Christophe De],
Accelerating the creation of instance segmentation training sets through bounding box annotation,
ICPR22(252-258)
IEEE DOI 2212
Training, Image segmentation, Systematics, Annotations, Image annotation, Manuals, Pattern recognition BibRef

Theodoridis, J.[Johannes], Hofmann, J.[Jessica], Maucher, J.[Johannes], Schilling, A.[Andreas],
Trapped in Texture Bias? A Large Scale Comparison of Deep Instance Segmentation,
ECCV22(VIII:609-627).
Springer DOI 2211
BibRef

Zhang, C.[Cheng], Pan, T.Y.[Tai-Yu], Chen, T.[Tianle], Zhong, J.[Jike], Fu, W.J.[Wen-Jin], Chao, W.L.[Wei-Lun],
Learning with Free Object Segments for Long-Tailed Instance Segmentation,
ECCV22(X:655-672).
Springer DOI 2211
BibRef

Alexandridis, K.P.[Konstantinos Panagiotis], Deng, J.K.[Jian-Kang], Nguyen, A.[Anh], Luo, S.[Shan],
Long-Tailed Instance Segmentation Using Gumbel Optimized Loss,
ECCV22(X:353-369).
Springer DOI 2211
BibRef

Chen, W.Y.[Wu-Yang], Du, X.Z.[Xian-Zhi], Yang, F.[Fan], Beyer, L.[Lucas], Zhai, X.H.[Xiao-Hua], Lin, T.Y.[Tsung-Yi], Chen, H.[Huizhong], Li, J.[Jing], Song, X.D.[Xiao-Dan], Wang, Z.Y.[Zhang-Yang], Zhou, D.[Denny],
A Simple Single-Scale Vision Transformer for Object Detection and Instance Segmentation,
ECCV22(X:711-727).
Springer DOI 2211
BibRef

Li, W.T.[Wen-Tong], Liu, W.Y.[Wen-Yu], Zhu, J.[Jianke], Cui, M.M.[Miao-Miao], Hua, X.S.[Xian-Sheng], Zhang, L.[Lei],
Box-Supervised Instance Segmentation with Level Set Evolution,
ECCV22(XXIX:1-18).
Springer DOI 2211
BibRef

Tang, C.F.[Chu-Feng], Xie, L.X.[Ling-Xi], Zhang, G.[Gang], Zhang, X.P.[Xiao-Peng], Tian, Q.[Qi], Hu, X.L.[Xiao-Lin],
Active Pointly-Supervised Instance Segmentation,
ECCV22(XXVIII:606-623).
Springer DOI 2211
BibRef

Zou, Y.L.[Yu-Liang], Zhang, Z.Z.[Zi-Zhao], Li, C.L.[Chun-Liang], Zhang, H.[Han], Pfister, T.[Tomas], Huang, J.B.[Jia-Bin],
Learning Instance-Specific Adaptation for Cross-Domain Segmentation,
ECCV22(XXXIII:459-476).
Springer DOI 2211
BibRef

Yang, P.[Pengwan], Asano, Y.M.[Yuki M.], Mettes, P.[Pascal], Snoek, C.G.M.[Cees G. M.],
Less Than Few: Self-shot Video Instance Segmentation,
ECCV22(XXXIV:449-466).
Springer DOI 2211
BibRef

Hu, Y.L.[Yun-Long], Zhang, C.Y.[Chong-Yang], Zhou, H.[Hao], Qian, Z.F.[Ze-Feng], Zhao, W.J.[Wei-Ji],
Boundary-Area Enhanced Module for Instance Segmentation,
ICIP22(1691-1695)
IEEE DOI 2211
Image segmentation, Fuses, Task analysis, instance segmentation, boundary segmentation, object detection, attention-based, feature enhancement BibRef

Du, K.W.[Kai-Wen], Wang, X.[Xiao], Yan, Y.[Yan], Lu, Y.[Yang], Wang, H.Z.[Han-Zi],
Egnet: A Novel Edge Guided Network for Instance Segmentation,
ICIP22(3868-3872)
IEEE DOI 2211
Image segmentation, Fuses, Image edge detection, Semantics, Feature extraction, Data mining, Instance segmentation, semantic enhancement BibRef

Gruber, M.[Maximiliane], Brand, F.[Fabian], Mosebach, A.[Alina], Seiler, J.[Jürgen], Kaup, A.[André],
Domain Adaptation for Unknown Image Distortions in Instance Segmentation,
ICIP22(1436-1440)
IEEE DOI 2211
Degradation, Training, Image segmentation, Visualization, Image coding, Training data, Object segmentation, Autonomous Driving BibRef

Wang, Z.Y.[Zhen-Yu], Li, Y.[Yali], Wang, S.J.[Sheng-Jin],
Noisy Boundaries: Lemon or Lemonade for Semi-supervised Instance Segmentation?,
CVPR22(16805-16814)
IEEE DOI 2210
Training, Image segmentation, Head, Costs, Resists, Pattern recognition, Scene analysis and understanding, Self- semi- meta- unsupervised learning BibRef

Zhou, T.F.[Tian-Fei], Wang, W.G.[Wen-Guan], Konukoglu, E.[Ender], Van Gool, L.J.[Luc J.],
Rethinking Semantic Segmentation: A Prototype View,
CVPR22(2572-2583)
IEEE DOI 2210
Training, Image analysis, Shape, Computational modeling, Semantics, Prototypes, grouping and shape analysis, Segmentation BibRef

Qiu, L.T.[Ling-Teng], Xiong, Z.Y.[Zhang-Yang], Wang, X.[Xuhao], Liu, K.K.[Ken-Kun], Li, Y.[Yihan], Chen, G.Y.[Guan-Ying], Han, X.G.[Xiao-Guang], Cui, S.G.[Shu-Guang],
ETHSeg: An Amodel Instance Segmentation Network and a Real-world Dataset for X-Ray Waste Inspection,
CVPR22(2273-2282)
IEEE DOI 2210
Image segmentation, Visualization, Annotations, Pipelines, Manuals, Inspection, Benchmark testing, Vision applications and systems BibRef

Cheng, B.[Bowen], Parkhi, O.[Omkar], Kirillov, A.[Alexander],
Pointly-Supervised Instance Segmentation,
CVPR22(2607-2616)
IEEE DOI 2210
Training, Annotations, Shape, Computer architecture, Pattern recognition, Segmentation, grouping and shape analysis BibRef

Lazarow, J.[Justin], Xu, W.J.[Wei-Jian], Tu, Z.W.[Zhuo-Wen],
Instance Segmentation with Mask-supervised Polygonal Boundary Transformers,
CVPR22(4372-4381)
IEEE DOI 2210
Deep learning, Shape, Computational modeling, Semantics, Computer architecture, Transformers, Segmentation, Deep learning architectures and techniques BibRef

Zhu, C.M.[Chen-Ming], Zhang, X.Y.[Xuan-Ye], Li, Y.[Yanran], Qiu, L.[Liangdong], Han, K.[Kai], Han, X.G.[Xiao-Guang],
SharpContour: A Contour-based Boundary Refinement Approach for Efficient and Accurate Instance Segmentation,
CVPR22(4382-4391)
IEEE DOI 2210
Analytical models, Costs, Shape, Computational modeling, Benchmark testing, Pattern recognition, Segmentation, grouping and shape analysis BibRef

Wolny, A.[Adrian], Yu, Q.[Qin], Pape, C.[Constantin], Kreshuk, A.[Anna],
Sparse Object-level Supervision for Instance Segmentation with Pixel Embeddings,
CVPR22(4392-4401)
IEEE DOI 2210
Training, Image segmentation, Annotations, Transfer learning, Semantics, Training data, Segmentation, Self- semi- meta- Transfer/low-shot/long-tail learning BibRef

Ke, L.[Lei], Danelljan, M.[Martin], Ding, H.H.[Heng-Hui], Tai, Y.W.[Yu-Wing], Tang, C.K.[Chi-Keung], Yu, F.[Fisher],
Mask-Free Video Instance Segmentation,
CVPR23(22857-22866)
IEEE DOI 2309
BibRef
Earlier: A1, A3, A2, A4, A5, A6:
Video Mask Transfiner for High-Quality Video Instance Segmentation,
ECCV22(XXVIII:731-747).
Springer DOI 2211
BibRef

Ke, L.[Lei], Danelljan, M.[Martin], Li, X.[Xia], Tai, Y.W.[Yu-Wing], Tang, C.K.[Chi-Keung], Yu, F.[Fisher],
Mask Transfiner for High-Quality Instance Segmentation,
CVPR22(4402-4411)
IEEE DOI 2210
Training, Convolutional codes, Image segmentation, Tensors, Costs, Shape, Segmentation, grouping and shape analysis BibRef

Wang, W.Y.[Wei-Yao], Feiszli, M.[Matt], Wang, H.[Heng], Malik, J.[Jitendra], Tran, D.[Du],
Open-World Instance Segmentation: Exploiting Pseudo Ground Truth From Learned Pairwise Affinity,
CVPR22(4412-4422)
IEEE DOI 2210
Training, Shape, Semantics, Taxonomy, Benchmark testing, Data models, Segmentation, grouping and shape analysis, retrieval BibRef

Zhang, T.[Tao], Wei, S.Q.[Shi-Qing], Ji, S.[Shunping],
E2EC: An End-to-End Contour-based Method for High-Quality High-Speed Instance Segmentation,
CVPR22(4433-4442)
IEEE DOI 2210
Image segmentation, Shape, Semantics, Graphics processing units, Computer architecture, Detectors, Predictive models, Segmentation, retrieval BibRef

He, Y.Y.[Yin-Yin], Zhang, P.Z.[Pei-Zhen], Wei, X.S.[Xiu-Shen], Zhang, X.Y.[Xiang-Yu], Sun, J.[Jian],
Relieving Long-tailed Instance Segmentation via Pairwise Class Balance,
CVPR22(6990-6999)
IEEE DOI 2210
Training, Transmission line matrix methods, Codes, Computational modeling, Computer architecture, retrieval BibRef

Nguyen, K.[Khoi], Todorovic, S.[Sinisa],
iFS-RCNN: An Incremental Few-shot Instance Segmenter,
CVPR22(7000-7009)
IEEE DOI 2210
Training, Measurement, Uncertainty, Shape, Performance gain, Pattern recognition, Transfer/low-shot/long-tail learning, grouping and shape analysis BibRef

Bailoni, A.[Alberto], Pape, C.[Constantin], Hütsch, N.[Nathan], Wolf, S.[Steffen], Beier, T.[Thorsten], Kreshuk, A.[Anna], Hamprecht, F.A.[Fred A.],
GASP, a generalized framework for agglomerative clustering of signed graphs and its application to Instance Segmentation,
CVPR22(11635-11645)
IEEE DOI 2210
Couplings, Systematics, Pipelines, Clustering algorithms, Predictive models, Prediction algorithms, Robustness, Segmentation, biological and cell microscopy BibRef

Dufour, R.[Rémi], Meurie, C.[Cyril], Strauss, C.[Clément], Lézoray, O.[Olivier],
Instance segmentation in fisheye images,
IPTA20(1-6)
IEEE DOI 2206
Image segmentation, Neural networks, Semantics, Transportation, Tools, Cameras, Task analysis, fisheye images, instance segmentation, data augmentation BibRef

Arents, J.[Janis], Lesser, B.[Bernd], Bizuns, A.[Andis], Kadikis, R.[Roberts], Buls, E.[Elvijs], Greitans, M.[Modris],
Synthetic Data of Randomly Piled, Similar Objects for Deep Learning-Based Object Detection,
CIAP22(II:706-717).
Springer DOI 2205
BibRef

Wang, L.[Lihao], Benmokhtar, R.[Rachid], Perrotton, X.[Xavier],
Interactive Deep Annotation as DARos: Object Detection Supervision for Efficient Instance Segmentation,
CIAP22(II:528-540).
Springer DOI 2205
BibRef

ul Moqeet Riaz, H.[Hamd], Benbarka, N.[Nuri], Hoefer, T.[Timon], Zell, A.[Andreas],
FourierMask: Instance Segmentation Using Fourier Mapping in Implicit Neural Networks,
CIAP22(II:587-598).
Springer DOI 2205
BibRef

Fang, Y.X.[Yu-Xin], Yang, S.S.[Shu-Sheng], Wang, X.G.[Xing-Gang], Li, Y.[Yu], Fang, C.[Chen], Shan, Y.[Ying], Feng, B.[Bin], Liu, W.Y.[Wen-Yu],
Instances as Queries,
ICCV21(6890-6899)
IEEE DOI 2203
Convolutional codes, Object detection, Detectors, Benchmark testing, Feature extraction, Task analysis, Segmentation, BibRef

Tan, F.[Fuwen], Yuan, J.B.[Jiang-Bo], Ordonez, V.[Vicente],
Instance-level Image Retrieval using Reranking Transformers,
ICCV21(12085-12095)
IEEE DOI 2203
Codes, Databases, Image retrieval, Feature extraction, Transformers, Search problems, Image and video retrieval, Recognition and classification BibRef

Papadopoulos, D.P.[Dim P.], Weber, E.[Ethan], Torralba, A.B.[Antonio B.],
Scaling up instance annotation via label propagation,
ICCV21(15344-15353)
IEEE DOI 2203
Image segmentation, Costs, Annotations, Pipelines, Object segmentation, Manuals, Scene analysis and understanding, Recognition and classification BibRef

Rumberger, J.L.[Josef Lorenz], Yu, X.Y.[Xiao-Yan], Hirsch, P.[Peter], Dohmen, M.[Melanie], Guarino, V.E.[Vanessa Emanuela], Mokarian, A.[Ashkan], Mais, L.[Lisa], Funke, J.[Jan], Kainmueller, D.[Dagmar],
How Shift Equivariance Impacts Metric Learning for Instance Segmentation,
ICCV21(7108-7116)
IEEE DOI 2203
Measurement, Training, Crops, Task analysis, Standards, Faces, Segmentation, grouping and shape, Medical, biological, Representation learning BibRef

Lan, S.Y.[Shi-Yi], Yu, Z.D.[Zhi-Ding], Choy, C.[Christopher], Radhakrishnan, S.[Subhashree], Liu, G.L.[Gui-Lin], Zhu, Y.K.[Yu-Ke], Davis, L.S.[Larry S.], Anandkumar, A.[Anima],
DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision,
ICCV21(3386-3396)
IEEE DOI 2203
Symbiosis, Measurement, Semantics, Benchmark testing, Real-time systems, Detection and localization in 2D and 3D, grouping and shape BibRef

Zang, Y.H.[Yu-Hang], Huang, C.[Chen], Loy, C.C.[Chen Change],
FASA: Feature Augmentation and Sampling Adaptation for Long-Tailed Instance Segmentation,
ICCV21(3437-3446)
IEEE DOI 2203
Training, Radio frequency, Schedules, Image segmentation, Costs, Transfer learning, Training data, BibRef

Biertimpel, D.[David], Shkodrani, S.[Sindi], Baslamisli, A.S.[Anil S.], Baka, N.[Nóra],
Prior to Segment: Foreground Cues for Weakly Annotated Classes in Partially Supervised Instance Segmentation,
ICCV21(2804-2813)
IEEE DOI 2203
Training, Head, Computer architecture, Cams, Detection and localization in 2D and 3D, Scene analysis and understanding BibRef

Cheng, Y.[Yuan], Lin, R.[Rui], Zhen, P.N.[Pei-Ning], Hou, T.S.[Tian-Shu], Ng, C.W.[Chiu Wa], Chen, H.B.[Hai-Bao], Yu, H.[Hao], Wong, N.[Ngai],
FASSST: Fast Attention Based Single-Stage Segmentation Net for Real-Time Instance Segmentation,
WACV22(2714-2722)
IEEE DOI 2202
Aggregates, Graphics processing units, Real-time systems, Artificial intelligence, Grouping and Shape BibRef

Yang, Y.Y.[Yu-Yuan], Hou, Y.L.[Ya-Li], Hou, Z.J.[Zhi-Jiang], Hao, X.L.[Xiao-Li], Shen, Y.[Yan],
Image-Level Supervised Instance Segmentation Using Instance-Wise Boundary,
ICIP21(1069-1073)
IEEE DOI 2201
Image segmentation, Annotations, Cams, Data mining, Instance segmentation, Weakly supervised, Image-level supervision BibRef

Rodríguez, M., Morel, J.M., Delon, J.,
Automatic Detection of Repeated Objects in Images,
ICIP21(2194-2198)
IEEE DOI 2201
Atomic measurements, Geometry, Image processing, Pipelines, Coherence, Filtering algorithms, image comparison, SIFT, NFA BibRef

Cerpa, A.[Alonso], Meza-Lovon, G.[Graciela], Fernández, M.E.L.[Manuel E. Loaiza],
Ensemble Learning to Perform Instance Segmentation over Synthetic Data,
ISVC21(II:313-324).
Springer DOI 2112
BibRef

Rossi, L.[Leonardo], Karimi, A.[Akbar], Prati, A.[Andrea],
Recursively Refined R-CNN: Instance Segmentation with Self-RoI Rebalancing,
CAIP21(I:476-486).
Springer DOI 2112
BibRef

Velesaca, H.O.[Henry O.], Suárez, P.L.[Patricia L.], Carpio, D.[Dario], Sappa, A.D.[Angel D.],
Synthesized Image Datasets: Towards an Annotation-Free Instance Segmentation Strategy,
ISVC21(I:131-143).
Springer DOI 2112
BibRef

Perreault, H.[Hughes], Bilodeau, G.A.[Guillaume-Alexandre], Saunier, N.[Nicolas], Héritier, M.[Maguelonne],
CenterPoly: real-time instance segmentation using bounding polygons,
AVVision21(2982-2991)
IEEE DOI 2112
Training, Codes, Annotations, Roads, Urban areas BibRef

Lyssenko, M.[Maria], Gladisch, C.[Christoph], Heinzemann, C.[Christian], Woehrle, M.[Matthias], Triebel, R.[Rudolph],
Instance Segmentation in CARLA: Methodology and Analysis for Pedestrian-oriented Synthetic Data Generation in Crowded Scenes,
ERCVAD21(988-996)
IEEE DOI 2112
Measurement, Annotations, Pipelines, Safety BibRef

Poucin, F.[Florentin], Kraus, A.[Andrea], Simon, M.[Martin],
Boosting Instance Segmentation with Synthetic Data: A study to overcome the limits of real world data sets,
ERCVAD21(945-953)
IEEE DOI 2112
Training, Industries, Image segmentation, Transfer learning, Neural networks BibRef

Vaswani, A.[Ashish], Ramachandran, P.[Prajit], Srinivas, A.[Aravind], Parmar, N.[Niki], Hechtman, B.[Blake], Shlens, J.[Jonathon],
Scaling Local Self-Attention for Parameter Efficient Visual Backbones,
CVPR21(12889-12899)
IEEE DOI 2111
Visualization, Image segmentation, Computational modeling, Transfer learning, Memory management, Object detection BibRef

Ghiasi, G.[Golnaz], Cui, Y.[Yin], Srinivas, A.[Aravind], Qian, R.[Rui], Lin, T.Y.[Tsung-Yi], Cubuk, E.D.[Ekin D.], Le, Q.V.[Quoc V.], Zoph, B.[Barret],
Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation,
CVPR21(2917-2927)
IEEE DOI 2111
Training, Image segmentation, Visualization, Additives, Systematics, Computational modeling BibRef

Shen, X.[Xing], Yang, J.[Jirui], Wei, C.[Chunbo], Deng, B.[Bing], Huang, J.Q.[Jian-Qiang], Hua, X.S.[Xian-Sheng], Cheng, X.L.[Xiao-Liang], Liang, K.W.[Ke-Wei],
DCT-Mask: Discrete Cosine Transform Mask Representation for Instance Segmentation,
CVPR21(8716-8725)
IEEE DOI 2111
Training, Schedules, Annotations, Complexity theory, Pattern recognition, Discrete cosine transforms BibRef

Ding, H.[Hao], Qiao, S.Y.[Si-Yuan], Yuille, A.L.[Alan L.], Shen, W.[Wei],
Deeply Shape-guided Cascade for Instance Segmentation,
CVPR21(8274-8284)
IEEE DOI 2111
Feedback loop, Codes, Shape, Bidirectional control, Feature extraction, Pattern recognition BibRef

Ganea, D.A.[Dan Andrei], Boom, B.[Bas], Poppe, R.[Ronald],
Incremental Few-Shot Instance Segmentation,
CVPR21(1185-1194)
IEEE DOI 2111
Location awareness, Training, Image segmentation, Memory management, Training data, Transfer functions BibRef

Zheng, Y.[Ye], Wu, J.H.[Jia-Hong], Qin, Y.Q.[Yong-Qiang], Zhang, F.[Faen], Cui, L.[Li],
Zero-Shot Instance Segmentation,
CVPR21(2593-2602)
IEEE DOI 2111
Training, Head, Protocols, Semantics, Detectors, Benchmark testing, Solids BibRef

Weng, Z.Z.[Zhen-Zhen], Ogut, M.G.[Mehmet Giray], Limonchik, S.[Shai], Yeung, S.[Serena],
Unsupervised Discovery of the Long-Tail in Instance Segmentation Using Hierarchical Self-Supervision,
CVPR21(2603-2612)
IEEE DOI 2111
Image segmentation, Annotations, Computational modeling, Supervised learning, Pattern recognition BibRef

Tian, Z.[Zhi], Shen, C.H.[Chun-Hua], Wang, X.L.[Xin-Long], Chen, H.[Hao],
BoxInst: High-Performance Instance Segmentation with Box Annotations,
CVPR21(5439-5448)
IEEE DOI 2111
Training, Schedules, Annotations, Color, Pattern recognition BibRef

Zhang, G.[Gang], Lu, X.[Xin], Tan, J.[Jingru], Li, J.M.[Jian-Min], Zhang, Z.X.[Zhao-Xiang], Li, Q.Q.[Quan-Quan], Hu, X.L.[Xiao-Lin],
RefineMask: Towards High-Quality Instance Segmentation with Fine-Grained Features,
CVPR21(6857-6865)
IEEE DOI 2111
Codes, Benchmark testing, Feature extraction, Pattern recognition, Computational efficiency BibRef

Wang, J.Q.[Jia-Qi], Zhang, W.W.[Wen-Wei], Zang, Y.H.[Yu-Hang], Cao, Y.H.[Yu-Hang], Pang, J.M.[Jiang-Miao], Gong, T.[Tao], Chen, K.[Kai], Liu, Z.W.[Zi-Wei], Loy, C.C.[Chen Change], Lin, D.[Dahua],
Seesaw Loss for Long-Tailed Instance Segmentation,
CVPR21(9690-9699)
IEEE DOI 2111
Training, Codes, Pipelines, Benchmark testing, Pattern recognition BibRef

Wang, X.G.[Xing-Gang], Feng, J.[Jiapei], Hu, B.[Bin], Ding, Q.[Qi], Ran, L.J.[Long-Jin], Chen, X.X.[Xiao-Xin], Liu, W.Y.[Wen-Yu],
Weakly-supervised Instance Segmentation via Class-agnostic Learning with Salient Images,
CVPR21(10220-10230)
IEEE DOI 2111
Training, Location awareness, Learning systems, Image segmentation, Codes, Merging BibRef

Nguyen, K.[Khoi], Todorovic, S.[Sinisa],
FAPIS: A Few-shot Anchor-free Part-based Instance Segmenter,
CVPR21(11094-11103)
IEEE DOI 2111
Training, Image segmentation, Image color analysis, Shape, Prototypes, Detectors BibRef

Sun, Y.H.[Yi-Hong], Kortylewski, A.[Adam], Yuille, A.L.[Alan L.],
Amodal Segmentation through Out-of-Task and Out-of-Distribution Generalization with a Bayesian Model,
CVPR22(1205-1214)
IEEE DOI 2210
Training, Image segmentation, Visualization, Shape, Neural networks, Predictive models, Segmentation, grouping and shape analysis, Self- semi- meta- unsupervised learning BibRef

Yuan, X.D.[Xiao-Ding], Kortylewski, A.[Adam], Sun, Y.H.[Yi-Hong], Yuille, A.L.[Alan L.],
Robust Instance Segmentation through Reasoning about Multi-Object Occlusion,
CVPR21(11136-11145)
IEEE DOI 2111
Deep learning, Image segmentation, Codes, Computer architecture, Cognition, Robustness BibRef

Hu, M.[Miao], Li, Y.[Yali], Fang, L.[Lu], Wang, S.J.[Sheng-Jin],
A2-FPN: Attention Aggregation based Feature Pyramid Network for Instance Segmentation,
CVPR21(15338-15347)
IEEE DOI 2111
Fuses, Aggregates, Semantics, Computer architecture, Feature extraction, Data mining BibRef

Tuan, T.A.[Tran Anh], Khoa, N.T.[Nguyen Tuan], Quan, T.M.[Tran Minh], Jeong, W.K.[Won-Ki],
ColorRL: Reinforced Coloring for End-to-End Instance Segmentation,
CVPR21(16722-16731)
IEEE DOI 2111
Image segmentation, Shape, Scalability, Reinforcement learning, Pattern recognition BibRef

Tang, C.F.[Chu-Feng], Chen, H.[Hang], Li, X.[Xiao], Li, J.M.[Jian-Min], Zhang, Z.X.[Zhao-Xiang], Hu, X.L.[Xiao-Lin],
Look Closer to Segment Better: Boundary Patch Refinement for Instance Segmentation,
CVPR21(13921-13930)
IEEE DOI 2111
Measurement, Codes, Benchmark testing, Business process re-engineering, Pattern recognition, Spatial resolution BibRef

Hsu, J.[Joy], Chiu, W.[Wah], Yeung, S.[Serena],
DARCNN: Domain Adaptive Region-based Convolutional Neural Network for Unsupervised Instance Segmentation in Biomedical Images,
CVPR21(1003-1012)
IEEE DOI 2111
Knowledge engineering, Image segmentation, Adaptive systems, Annotations, Benchmark testing, Pattern recognition BibRef

Lee, J.[Jungbeom], Yi, J.[Jihun], Shin, C.[Chaehun], Yoon, S.[Sungroh],
BBAM: Bounding Box Attribution Map for Weakly Supervised Semantic and Instance Segmentation,
CVPR21(2643-2651)
IEEE DOI 2111
Image segmentation, Annotations, Semantics, Detectors, Benchmark testing, Generators BibRef

Kim, M.[Myungchul], Woo, S.[Sanghyun], Kim, D.[Dahun], Kweon, I.S.[In So],
The Devil is in the Boundary: Exploiting Boundary Representation for Basis-based Instance Segmentation,
WACV21(928-937)
IEEE DOI 2106
Measurement, Image segmentation, Image resolution, Shape, Predictive models BibRef

Mercier, J.P.[Jean-Philippe], Garon, M.[Mathieu], Giguère, P.[Philippe], Lalonde, J.F.[Jean-François],
Deep Template-based Object Instance Detection,
WACV21(1506-1515)
IEEE DOI 2106
Training, Matched filters, Service robots, Toy manufacturing industry, Object detection BibRef

Hwang, J.[Jaedong], Kim, S.[Seohyun], Son, J.[Jeany], Han, B.H.[Bo-Hyung],
Weakly Supervised Instance Segmentation by Deep Community Learning,
WACV21(1019-1028)
IEEE DOI 2106
Training, Neural networks, Semantics, Object detection, Detectors, Feature extraction, Proposals BibRef

Goel, K.[Kratarth], Srinivasan, P.[Praveen], Tariq, S.[Sarah], Philbin, J.[James],
QuadroNet: Multi-Task Learning for Real-Time Semantic Depth Aware Instance Segmentation,
WACV21(315-324)
IEEE DOI 2106
Training, Image segmentation, Laser radar, Semantics, Object detection, Network architecture BibRef

Liu, Z.C.[Zi-Chen], Liew, J.H.[Jun Hao], Chen, X.Y.[Xiang-Yu], Feng, J.S.[Jia-Shi],
DANCE: A Deep Attentive Contour Model for Efficient Instance Segmentation,
WACV21(345-354)
IEEE DOI 2106
Deformable models, Training, Computational modeling, Pipelines, Real-time systems BibRef

Liu, X.L.[Xiao-Long], Hou, Y.Q.[Yu-Qing], Yao, A.[Anbang], Chen, Y.R.[Yu-Rong], Li, K.Q.[Ke-Qiang],
CASNet: Common Attribute Support Network for image instance and panoptic segmentation,
ICPR21(8469-8475)
IEEE DOI 2105
Training, Bridges, Image segmentation, Semantics, Clustering algorithms, Object detection, Prediction algorithms BibRef

Rossi, L.[Leonardo], Karimi, A.[Akbar], Prati, A.[Andrea],
A Novel Region of Interest Extraction Layer for Instance Segmentation,
ICPR21(2203-2209)
IEEE DOI 2105
Architecture, Neural networks, Computer architecture, Object detection, Feature extraction, Pattern recognition BibRef

Li, X.R.[Xi-Rong], Wan, W.C.[Wen-Cui], Zhou, Y.[Yang], Zhao, J.C.[Jian-Chun], Wei, Q.J.[Qi-Jie], Rong, J.[Junbo], Zhou, P.Y.[Peng-Yi], Xu, L.M.[Li-Min], Lang, L.J.[Li-Juan], Liu, Y.Y.[Yu-Ying], Niu, C.Z.[Cheng-Zhi], Ding, D.Y.[Da-Yong], Jin, X.M.[Xue-Min],
Deep Multiple Instance Learning with Spatial Attention for ROP Case Classification, Instance Selection and Abnormality Localization,
ICPR21(7293-7298)
IEEE DOI 2105
Location awareness, Visualization, Retinopathy, Image color analysis, Retina, Pattern recognition, Task analysis, abnormality localization BibRef

Riaz, H.U.M.[Hamd Ul Moqeet], Benbarka, N.[Nuri], Zell, A.[Andreas],
FourierNet: Compact Mask Representation for Instance Segmentation Using Differentiable Shape Decoders,
ICPR21(7833-7840)
IEEE DOI 2105
Training, Image resolution, Shape, Transforms, Detectors, Real-time systems, Decoding, Instance segmentation, Fourier series, differentiable algorithms BibRef

Heidecker, F.[Florian], Hannan, A.[Abdul], Bieshaar, M.[Maarten], Sick, B.[Bernhard],
Towards Corner Case Detection by Modeling the Uncertainty of Instance Segmentation Networks,
HCAU20(361-374).
Springer DOI 2103
BibRef

Schneegans, J.[Jan], Bieshaar, M.[Maarten], Heidecker, F.[Florian], Sick, B.[Bernhard],
Intelligent and Interactive Video Annotation for Instance Segmentation Using Siamese Neural Networks,
HCAU20(375-389).
Springer DOI 2103
BibRef

Ito, S.[Satoshi], Kubota, S.[Susumu],
Point Proposal Based Instance Segmentation with Rectangular Masks for Robot Picking Task,
ACCV20(III:641-653).
Springer DOI 2103
BibRef

Yang, L., Li, H., Wu, Q., Meng, F., Ngi Ngan, K.,
Mono is Enough: Instance Segmentation from Single Annotated Sample,
VCIP20(120-123)
IEEE DOI 2102
Image segmentation, Distortion, Brightness, Data models, Annotations, Training data, Task analysis, Instance Segmentation, Data Augmentation BibRef

Wang, X.L.[Xin-Long], Kong, T.[Tao], Shen, C.H.[Chun-Hua], Jiang, Y.N.[Yu-Ning], Li, L.[Lei],
SOLO: Segmenting Objects by Locations,
ECCV20(XVIII:649-665).
Springer DOI 2012
Code, Segmentation.
WWW Link. BibRef

Mais, L.[Lisa], Hirsch, P.[Peter], Kainmueller, D.[Dagmar],
PatchPerPix for Instance Segmentation,
ECCV20(XXV:288-304).
Springer DOI 2011
BibRef

Chen, X.[Xier], Lian, Y.C.[Yan-Chao], Jiao, L.C.[Li-Cheng], Wang, H.R.[Hao-Ran], Gao, Y.J.[Yan-Jie], Shi, L.L.[Ling-Ling],
Supervised Edge Attention Network for Accurate Image Instance Segmentation,
ECCV20(XXVII:617-631).
Springer DOI 2011
BibRef

Laradji, I.H., Rostamzadeh, N., Pinheiro, P.O., Vazquez, D., Schmidt, M.,
Proposal-Based Instance Segmentation With Point Supervision,
ICIP20(2126-2130)
IEEE DOI 2011
Proposals, Training, Image segmentation, Task analysis, Predictive models, Automobiles, Autonomous vehicles, weak supervision BibRef

Cheng, T.H.[Tian-Heng], Wang, X.G.[Xing-Gang], Huang, L.C.[Li-Chao], Liu, W.Y.[Wen-Yu],
Boundary-preserving Mask R-CNN,
ECCV20(XIV:660-676).
Springer DOI 2011
BibRef

Wang, T.[Tao], Li, Y.[Yu], Kang, B.Y.[Bing-Yi], Li, J.[Junnan], Liew, J.H.[Jun-Hao], Tang, S.[Sheng], Feng, S.H.J.[Steven Hoi-Jiashi],
The Devil Is in Classification: A Simple Framework for Long-tail Instance Segmentation,
ECCV20(XIV:728-744).
Springer DOI 2011
BibRef

Fan, Q.[Qi], Ke, L.[Lei], Pei, W.J.[Wen-Jie], Tang, C.K.[Chi-Keung], Tai, Y.W.[Yu-Wing],
Commonality-parsing Network Across Shape and Appearance for Partially Supervised Instance Segmentation,
ECCV20(VIII:379-396).
Springer DOI 2011
BibRef

Wei, F.Y.[Fang-Yun], Sun, X.[Xiao], Li, H.Y.[Hong-Yang], Wang, J.D.[Jing-Dong], Lin, S.[Stephen],
Point-set Anchors for Object Detection, Instance Segmentation and Pose Estimation,
ECCV20(X:527-544).
Springer DOI 2011
BibRef

Arun, A.[Aditya], Jawahar, C.V., Kumar, M.P.[M. Pawan],
Weakly Supervised Instance Segmentation by Learning Annotation Consistent Instances,
ECCV20(XXVIII:254-270).
Springer DOI 2011
BibRef

Homayounfar, N.[Namdar], Xiong, Y.[Yuwen], Liang, J.[Justin], Ma, W.C.[Wei-Chiu], Urtasun, R.[Raquel],
Levelset R-CNN: A Deep Variational Method for Instance Segmentation,
ECCV20(XXIII:555-571).
Springer DOI 2011
BibRef

Tian, Z.[Zhi], Shen, C.H.[Chun-Hua], Chen, H.[Hao],
Conditional Convolutions for Instance Segmentation,
ECCV20(I:282-298).
Springer DOI 2011
BibRef

Zhou, Y., Wang, X., Jiao, J., Darrell, T.J., Yu, F.,
Learning Saliency Propagation for Semi-Supervised Instance Segmentation,
CVPR20(10304-10313)
IEEE DOI 2008
Shape, Image segmentation, Head, Feature extraction, Task analysis, Semantics, Message passing BibRef

Cao, J., Cholakkal, H., Anwer, R.M., Khan, F.S., Pang, Y., Shao, L.,
D2Det: Towards High Quality Object Detection and Instance Segmentation,
CVPR20(11482-11491)
IEEE DOI 2008
Proposals, Detectors, Object detection, Feature extraction, Standards, Training, Benchmark testing BibRef

Zeni, L.F., Jung, C.R.,
Distilling Knowledge from Refinement in Multiple Instance Detection Networks,
DeepVision20(3324-3333)
IEEE DOI 2008
Proposals, Feature extraction, Training, Detectors, Object detection, Knowledge engineering, Task analysis BibRef

Peng, S., Jiang, W., Pi, H., Li, X., Bao, H., Zhou, X.,
Deep Snake for Real-Time Instance Segmentation,
CVPR20(8530-8539)
IEEE DOI 2008
Convolution, Image segmentation, Standards, Pipelines, Kernel, Strain, Real-time systems BibRef

Chen, H., Sun, K., Tian, Z., Shen, C., Huang, Y., Yan, Y.,
BlendMask: Top-Down Meets Bottom-Up for Instance Segmentation,
CVPR20(8570-8578)
IEEE DOI 2008
Agriculture, Shape, Convolution, Detectors, Proposals, Task analysis, Computational complexity BibRef

Liang, J., Homayounfar, N., Ma, W., Xiong, Y., Hu, R., Urtasun, R.,
PolyTransform: Deep Polygon Transformer for Instance Segmentation,
CVPR20(9128-9137)
IEEE DOI 2008
Feature extraction, Task analysis, Image segmentation, Proposals, Semantics, Computational modeling, Measurement BibRef

Fan, Z., Yu, J., Liang, Z., Ou, J., Gao, C., Xia, G., Li, Y.,
FGN: Fully Guided Network for Few-Shot Instance Segmentation,
CVPR20(9169-9178)
IEEE DOI 2008
Task analysis, Image segmentation, Semantics, Training, Detectors, Proposals, Adaptation models BibRef

Wang, Y.Q.[Yu-Qing], Xu, Z.L.[Zhao-Liang], Shen, H.[Hao], Cheng, B.S.[Bao-Shan], Yang, L.R.[Li-Rong],
CenterMask: Single Shot Instance Segmentation With Point Representation,
CVPR20(9310-9318)
IEEE DOI 2008
Shape, Image segmentation, Head, Feature extraction, Detectors, Visualization BibRef

Zhang, R., Tian, Z., Shen, C., You, M., Yan, Y.,
Mask Encoding for Single Shot Instance Segmentation,
CVPR20(10223-10232)
IEEE DOI 2008
Encoding, Task analysis, Detectors, Feature extraction, Pipelines, Principal component analysis, Training BibRef

Lin, C., Hung, Y., Feris, R., He, L.,
Video Instance Segmentation Tracking With a Modified VAE Architecture,
CVPR20(13144-13154)
IEEE DOI 2008
Task analysis, Decoding, Proposals, Motion segmentation, Object segmentation, Target tracking, Image segmentation BibRef

Lee, Y., Park, J.,
CenterMask: Real-Time Anchor-Free Instance Segmentation,
CVPR20(13903-13912)
IEEE DOI 2008
Detectors, Feature extraction, Real-time systems, Head, Object detection, Proposals, Computer architecture BibRef

Chu, X., Zheng, A., Zhang, X., Sun, J.,
Detection in Crowded Scenes: One Proposal, Multiple Predictions,
CVPR20(12211-12220)
IEEE DOI 2008
Proposals, Detectors, Object detection, Color, Pipelines, Neural networks BibRef

Wang, Q.[Qiong], Zhang, L.[Lu], Kpalma, K.[Kidiyo],
A Semantics-guided Warping for Semi-supervised Video Object Instance Segmentation,
ICIAR20(I:186-195).
Springer DOI 2007
BibRef

Ma, J.[Jin], Pang, S.M.[Shan-Min], Yang, B.[Bo], Zhu, J.H.[Ji-Hua], Li, Y.C.[Yao-Chen],
Spatial-Content Image Search in Complex Scenes,
WACV20(2492-2500)
IEEE DOI 2006
Code, Image Search.
WWW Link. Visualization, Semantics, Image retrieval, Feature extraction, Image representation, Object detection BibRef

Sharma, K., Gold, M., Zurbruegg, C., Leal-Taixé, L., Wegner, J.D.,
HistoNet: Predicting size histograms of object instances,
WACV20(3626-3634)
IEEE DOI 2006
Histograms, Image segmentation, Task analysis, Estimation, Computer architecture, Training, Cancer BibRef

Royer, A., Lampert, C.H.,
Localizing Grouped Instances for Efficient Detection in Low-Resource Scenarios,
WACV20(1716-1725)
IEEE DOI 2006
Detectors, Object detection, Image resolution, Task analysis, Computer architecture, Pipelines, Training BibRef

Xu, S., Lan, S., Zhu, Q.,
MaskPlus: Improving Mask Generation for Instance Segmentation,
WACV20(2019-2027)
IEEE DOI 2006
Image segmentation, Semantics, Training, Proposals, Feature extraction, Task analysis, Object recognition BibRef

Shashidhara, B.M., Scott, M., Marburg, A.,
Instance Segmentation of Benthic Scale Worms at a Hydrothermal Site,
WACV20(1303-1312)
IEEE DOI 2006
Grippers, Vents, Image segmentation, Pipelines, Training, Training data, Cameras BibRef

Wang, Y., Ramanan, D., Hebert, M.,
Meta-Learning to Detect Rare Objects,
ICCV19(9924-9933)
IEEE DOI 2004
convolutional neural nets, image classification, learning (artificial intelligence), object detection, Training BibRef

Hu, T., Mettes, P.S., Huang, J., Snoek, C.G.M.,
SILCO: Show a Few Images, Localize the Common Object,
ICCV19(5066-5075)
IEEE DOI 2004
convolutional neural nets, feature extraction, graph theory, image classification, learning (artificial intelligence), Machine learning BibRef

Deng, Z., Kong, Q., Murakami, T.,
Towards Efficient Instance Segmentation with Hierarchical Distillation,
TASKCV19(3243-3249)
IEEE DOI 2004
image segmentation, learning (artificial intelligence), object detection, distills pair-wise quantized feature maps, Knowledge distillation BibRef

Fang, H., Sun, J., Wang, R., Gou, M., Li, Y., Lu, C.,
InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting,
ICCV19(682-691)
IEEE DOI 2004
Code, Segmentation.
WWW Link. convolutional neural nets, image annotation, image sampling, image segmentation, object detection, probability, Measurement BibRef

Ge, W., Huang, W., Guo, S., Scott, M.,
Label-PEnet: Sequential Label Propagation and Enhancement Networks for Weakly Supervised Instance Segmentation,
ICCV19(3344-3353)
IEEE DOI 2004
image classification, image representation, image segmentation, learning (artificial intelligence), object detection, Task analysis BibRef

Shaban, A., Rahimi, A., Bansal, S., Gould, S., Boots, B., Hartley, R.,
Learning to Find Common Objects Across Few Image Collections,
ICCV19(5116-5125)
IEEE DOI 2004
belief networks, greedy algorithms, inference mechanisms, learning (artificial intelligence), minimisation, Graphical models BibRef

Fu, C., Berg, T.L.[Tamara L.], Berg, A.C.[Alexander C.],
IMP: Instance Mask Projection for High Accuracy Semantic Segmentation of Things,
ICCV19(5177-5186)
IEEE DOI 2004
backpropagation, image segmentation, object detection, backpropagation, baseline semantic segmentation results, Object detection BibRef

Yang, L., Fan, Y., Xu, N.,
Video Instance Segmentation,
ICCV19(5187-5196)
IEEE DOI 2004
convolutional neural nets, image segmentation, multimedia Web sites, object detection, object tracking, Object segmentation BibRef

Nassar, A.S.[Ahmed Samy], d'Aronco, S.[Stefano], Lefèvre, S.[Sébastien], Wegner, J.D.[Jan D.],
Geograph: Graph-based Multi-view Object Detection with Geometric Cues End-to-end,
ECCV20(VII:488-504).
Springer DOI 2011
BibRef
Earlier: A1, A3, A4, Only:
Simultaneous Multi-View Instance Detection With Learned Geometric Soft-Constraints,
ICCV19(6558-6567)
IEEE DOI 2004
geometry, learning (artificial intelligence), object detection, robust cross-view object detection, geometric soft constraints, Pose estimation BibRef

Sofiiuk, K., Sofiyuk, K., Barinova, O., Konushin, A., Barinova, O.,
AdaptIS: Adaptive Instance Selection Network,
ICCV19(7354-7362)
IEEE DOI 2004
Code, Segmentation.
WWW Link. image segmentation, object detection, AdaIN layers, pixel-accurate object masks, semantic segmentation pipeline, Aerospace electronics BibRef

Xu, W., Wang, H., Qi, F., Lu, C.,
Explicit Shape Encoding for Real-Time Instance Segmentation,
ICCV19(5167-5176)
IEEE DOI 2004
image segmentation, object detection, polynomials, tensors, object detection, explicit shape encoding, Training BibRef

Fan, R.C.[Ruo-Chen], Hou, Q.B.[Qi-Bin], Cheng, M.M.[Ming-Ming], Yu, G.[Gang], Martin, R.R.[Ralph R.], Hu, S.M.[Shi-Min],
Associating Inter-image Salient Instances for Weakly Supervised Semantic Segmentation,
ECCV18(IX: 371-388).
Springer DOI 1810
BibRef

Luc, P.[Pauline], Couprie, C.[Camille], Le Cun, Y.L.[Yann L.], Verbeek, J.[Jakob],
Predicting Future Instance Segmentation by Forecasting Convolutional Features,
ECCV18(IX: 593-608).
Springer DOI 1810
BibRef

Luc, P.[Pauline], Neverova, N., Couprie, C.[Camille], Verbeek, J.[Jakob], Le Cun, Y.L.[Yann L.],
Predicting Deeper into the Future of Semantic Segmentation,
ICCV17(648-657)
IEEE DOI 1802
feedforward neural nets, image colour analysis, image resolution, image segmentation, image sequences, Training BibRef

Li, Y., Qi, H., Dai, J., Ji, X., Wei, Y.,
Fully Convolutional Instance-Aware Semantic Segmentation,
CVPR17(4438-4446)
IEEE DOI 1711
Convolution, Convolutional codes, Image segmentation, Object segmentation, Proposals, Semantics BibRef

Yao, J.[Jian], Boben, M.[Marko], Fidler, S.[Sanja], Urtasun, R.[Raquel],
Real-time coarse-to-fine topologically preserving segmentation,
CVPR15(2947-2955)
IEEE DOI 1510
BibRef

Gupta, A.[Agrim], Dollar, P.[Piotr], Girshick, R.[Ross],
LVIS: A Dataset for Large Vocabulary Instance Segmentation,
CVPR19(5351-5359).
IEEE DOI 2002
BibRef

Araslanov, N.[Nikita], Rothkopf, C.A.[Constantin A.], Roth, S.[Stefan],
Actor-Critic Instance Segmentation,
CVPR19(8229-8238).
IEEE DOI 2002
BibRef

Liu, S., Qi, L., Qin, H., Shi, J., Jia, J.,
Path Aggregation Network for Instance Segmentation,
CVPR18(8759-8768)
IEEE DOI 1812
Proposals, Feature extraction, Task analysis, Image segmentation, Object detection, Training, Semantics BibRef

Chen, L., Hermans, A., Papandreou, G., Schroff, F., Wang, P., Adam, H.,
MaskLab: Instance Segmentation by Refining Object Detection with Semantic and Direction Features,
CVPR18(4013-4022)
IEEE DOI 1812
Semantics, Agriculture, Image segmentation, Object detection, Convolution, Feature extraction, Encoding BibRef

Neven, D.[Davy], de Brabandere, B.[Bert], Proesmans, M.[Marc], Van Gool, L.J.[Luc J.],
Instance Segmentation by Jointly Optimizing Spatial Embeddings and Clustering Bandwidth,
CVPR19(8829-8837).
IEEE DOI 2002
BibRef

Qi, L.[Lu], Jiang, L.[Li], Liu, S.[Shu], Shen, X.Y.[Xiao-Yong], Jia, J.Y.[Jia-Ya],
Amodal Instance Segmentation With KINS Dataset,
CVPR19(3009-3018).
IEEE DOI 2002
BibRef

Chen, K.[Kai], Pang, J.M.[Jiang-Miao], Wang, J.Q.[Jia-Qi], Xiong, Y.[Yu], Li, X.X.[Xiao-Xiao], Sun, S.Y.[Shu-Yang], Feng, W.[Wansen], Liu, Z.W.[Zi-Wei], Shi, J.P.[Jian-Ping], Ouyang, W.L.[Wan-Li], Loy, C.C.[Chen Change], Lin, D.[Dahua],
Hybrid Task Cascade for Instance Segmentation,
CVPR19(4969-4978).
IEEE DOI 2002
BibRef

Shang, C., Wu, Q., Meng, F., Xu, L.,
Instance Segmentation by Learning Deep Feature in Embedding Space,
ICIP19(2444-2448)
IEEE DOI 1910
Instance Segmentation, Instance Discrimination Network, Embedding Space, Deep Feature BibRef

Liu, Y.F.[Yan-Feng], Psota, E.T.[Eric T.], Pérez, L.C.[Lance C.],
Layered Embeddings for Amodal Instance Segmentation,
ICIAR19(I:102-111).
Springer DOI 1909
Code, Segmentation. Code available:
WWW Link. BibRef

Couprie, C.[Camille], Luc, P.[Pauline], Verbeek, J.[Jakob],
Joint Future Semantic and Instance Segmentation Prediction,
AnticipateBeh18(III:154-168).
Springer DOI 1905
BibRef

Halupka, K., Garnavi, R., Moore, S.,
Deep Semantic Instance Segmentation of Tree-Like Structures Using Synthetic Data,
WACV19(1713-1722)
IEEE DOI 1904
data analysis, feature extraction, image segmentation, learning (artificial intelligence), neural nets, Periodic structures BibRef

Follmann, P.[Patrick], Nig, R.K.[Rebecca Kö], Rtinger, P.H.[Philipp Hä], Klostermann, M.[Michael], Ttger, T.B.[Tobias Bö],
Learning to See the Invisible: End-to-End Trainable Amodal Instance Segmentation,
WACV19(1328-1336)
IEEE DOI 1904
image segmentation, learning (artificial intelligence), object detection, COCOA cls, D2S amodal, COCO amodal dataset, BibRef

Li, K.[Ke], Malik, J.[Jitendra],
Amodal Instance Segmentation,
ECCV16(II: 677-693).
Springer DOI 1611
predict the region encompassing both visible and occluded parts of each object. BibRef

Li, K.[Ke], Hariharan, B.[Bharath], Malik, J.[Jitendra],
Iterative Instance Segmentation,
CVPR16(3659-3667)
IEEE DOI 1612
BibRef

Li, Z.X.[Zuo-Xin], Zhou, F.Q.[Fu-Qiang], Yang, L.[Lu],
Fast Single Shot Instance Segmentation,
ACCV18(IV:257-272).
Springer DOI 1906
BibRef

Manohar, K.V., Niitani, Y.[Yusuke],
An End-to-End Tree Based Approach for Instance Segmentation,
POCV18(V:521-527).
Springer DOI 1905
BibRef

Liu, Y., Wang, R., Shan, S., Chen, X.,
Structure Inference Net: Object Detection Using Scene-Level Context and Instance-Level Relationships,
CVPR18(6985-6994)
IEEE DOI 1812
Object detection, Feature extraction, Logic gates, Visualization, Detectors, Context modeling, Image edge detection BibRef

Zhou, Y.Z.[Yan-Zhao], Zhu, Y.[Yi], Ye, Q.X.[Qi-Xiang], Qiu, Q.[Qiang], Jiao, J.B.[Jian-Bin],
Weakly Supervised Instance Segmentation Using Class Peak Response,
CVPR18(3791-3800)
IEEE DOI 1812
Image segmentation, Visualization, Training, Semantics, Proposals, Image color analysis, Kernel BibRef

Liu, Y.D.[Yi-Ding], Yang, S.[Siyu], Li, B.[Bin], Zhou, W.G.[Wen-Gang], Xu, J.Z.[Ji-Zheng], Li, H.Q.A.[Hou-Qi-Ang], Lu, Y.[Yan],
Affinity Derivation and Graph Merge for Instance Segmentation,
ECCV18(III: 708-724).
Springer DOI 1810
BibRef

Novotny, D.[David], Albanie, S.[Samuel], Larlus, D.[Diane], Vedaldi, A.[Andrea],
Semi-convolutional Operators for Instance Segmentation,
ECCV18(I: 89-105).
Springer DOI 1810
BibRef

Margffoy-Tuay, E.[Edgar], Pérez, J.C.[Juan C.], Botero, E.[Emilio], Arbeláez, P.[Pablo],
Dynamic Multimodal Instance Segmentation Guided by Natural Language Queries,
ECCV18(XI: 656-672).
Springer DOI 1810
BibRef

Xu, W.Q.[Wen-Qiang], Li, Y.L.[Yong-Lu], Lu, C.W.[Ce-Wu],
SRDA: Generating Instance Segmentation Annotation via Scanning, Reasoning and Domain Adaptation,
ECCV18(XII: 124-140).
Springer DOI 1810
BibRef

Pham, T.[Trung], Kumar, B.G.V.[B. G. Vijay], Do, T.T.[Thanh-Toan], Carneiro, G.[Gustavo], Reid, I.D.[Ian D.],
Bayesian Semantic Instance Segmentation in Open Set World,
ECCV18(X: 3-18).
Springer DOI 1810
BibRef

Li, Y.[Yao], Liu, L.Q.[Ling-Qiao], Shen, C.H.[Chun-Hua], van den Hengel, A.[Anton],
Image Co-Localization by Mimicking a Good Detector's Confidence Score Distribution,
ECCV16(II: 19-34).
Springer DOI 1611
identify each instance in multiple images. BibRef

Chen, Y.T.[Yi-Ting], Liu, X.K.[Xiao-Kai], Yang, M.H.[Ming-Hsuan],
Multi-instance object segmentation with occlusion handling,
CVPR15(3470-3478)
IEEE DOI 1510
BibRef

Liu, B.Y.[Bu-Yu], He, X.M.[Xu-Ming],
Multiclass semantic video segmentation with object-level active inference,
CVPR15(4286-4294)
IEEE DOI 1510
BibRef

Liu, B.Y.[Bu-Yu], He, X.M.[Xu-Ming], Gould, S.[Stephen],
Multi-class Semantic Video Segmentation with Exemplar-Based Object Reasoning,
WACV15(1014-1021)
IEEE DOI 1503
Cognition BibRef

Chang, F.J.[Feng-Ju], Lin, Y.Y.[Yen-Yu], Hsu, K.J.[Kuang-Jui],
Multiple Structured-Instance Learning for Semantic Segmentation with Uncertain Training Data,
CVPR14(360-367)
IEEE DOI 1409
BibRef

He, X.M.[Xu-Ming], Gould, S.[Stephen],
An Exemplar-Based CRF for Multi-instance Object Segmentation,
CVPR14(296-303)
IEEE DOI 1409
BibRef
Earlier:
Multi-instance Object Segmentation with Exemplars,
GMSU13(1-4)
IEEE DOI 1403
Markov processes BibRef

Vezhnevets, A.[Alexander], Ferrari, V.[Vittorio],
Associative Embeddings for Large-Scale Knowledge Transfer with Self-Assessment,
CVPR14(1987-1994)
IEEE DOI 1409
ImageNet BibRef

Vezhnevets, A.[Alexander], Buhmann, J.M.[Joachim M.], Ferrari, V.[Vittorio],
Active learning for semantic segmentation with expected change,
CVPR12(3162-3169).
IEEE DOI 1208
BibRef

Vezhnevets, A.[Alexander], Ferrari, V.[Vittorio], Buhmann, J.M.[Joachim M.],
Weakly supervised structured output learning for semantic segmentation,
CVPR12(845-852).
IEEE DOI 1208
BibRef
Earlier:
Weakly supervised semantic segmentation with a multi-image model,
ICCV11(643-650).
IEEE DOI 1201
BibRef

Vezhnevets, A.[Alexander], Buhmann, J.M.[Joachim M.],
Towards weakly supervised semantic segmentation by means of multiple instance and multitask learning,
CVPR10(3249-3256).
IEEE DOI 1006

See also Agnostic Domain Adaptation. BibRef

Chapter on 2-D Region Segmentation Techniques, Snakes, Active Contours continues in
Counting Instances, Counting Objects .


Last update:May 6, 2024 at 15:50:14