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DARPA87(507-520).
See also Sigma Image Understanding System, The. Find segments (homogeneous regions), then find instances which
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Determinantal Point Processes, Object Detection, Crowd Detection
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Weakly supervised instance segmentation,
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Veins, Binary codes, Search problems, Computational efficiency,
Task analysis, Optimization, Indexing, Object search, binary code,
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Silva, C.R.[Cristiano Rosa],
Ferreira, P.H.G.[Pedro Henrique Guimarães],
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Xu, Y.,
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IEEE DOI
2102
Proposals, Annotations, Object detection, Training,
Image segmentation, Detectors, Task analysis, pyramidal network
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IEEE DOI
2103
Semantics, Detectors, Image segmentation, Object detection,
Task analysis, Proposals, Image reconstruction,
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IEEE DOI
2104
Feature extraction, Semantics, Image segmentation, Visualization,
Task analysis, Object detection, Convolution, RoIAlign
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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
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Wang, H.[Hui],
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Qian, W.L.[Wan-Li],
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RS(13), No. 8, 2021, pp. xx-yy.
DOI Link
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Lu, J.Y.[Jun-Yan],
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An Instance Segmentation Based Framework for Large-Sized
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RS(13), No. 9, 2021, pp. xx-yy.
DOI Link
2105
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Pang, J.M.[Jiang-Miao],
Chen, K.[Kai],
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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],
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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
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Liu, N.[Nian],
Zhao, W.B.[Wang-Bo],
Shao, L.[Ling],
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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
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Wu, Z.T.[Zi-Tong],
Hou, B.[Biao],
Ren, B.[Bo],
Ren, Z.L.[Zhong-Le],
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Jiao, L.C.[Li-Cheng],
A Deep Detection Network Based on Interaction of Instance
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RS(13), No. 13, 2021, pp. xx-yy.
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2107
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Zeng, X.F.[Xiang-Feng],
Wei, S.J.[Shun-Jun],
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Fan, F.[Fan],
CPISNet: Delving into Consistent Proposals of Instance Segmentation
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RS(13), No. 14, 2021, pp. xx-yy.
DOI Link
2107
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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
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Zhan, Y.[Yu],
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Instance search via instance level segmentation and feature
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JVCIR(79), 2021, pp. 103253.
Elsevier DOI
2109
Instance search, Instance segmentation, CNN
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Gominski, D.[Dimitri],
Gouet-Brunet, V.[Valérie],
Chen, L.M.[Li-Ming],
Connecting Images through Sources: Exploring Low-Data, Heterogeneous
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RS(13), No. 16, 2021, pp. xx-yy.
DOI Link
2109
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Hao, S.Y.[Sheng-Yu],
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Elsevier DOI
2110
Instance segmentation, Weakly supervised, Multi-priors, Bounding box annotations
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Yang, F.[Feng],
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Shu, W.Q.[Wen-Qiang],
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Accurate Instance Segmentation for Remote Sensing Images via Adaptive
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Wang, T.[Tao],
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SODAR: Exploring Locally Aggregated Learning of Mask Representations
for Instance Segmentation,
IP(31), 2022, pp. 839-851.
IEEE DOI
2201
Microprocessors, Image segmentation,
Convolution, Predictive models, Shape, Computational modeling,
mask representation
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Bolya, D.[Daniel],
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Lee, Y.J.[Yong Jae],
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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)
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Bolya, D.[Daniel],
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Springer DOI
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Zhang, X.L.[Xiao-Liang],
Li, H.L.[Hong-Liang],
Meng, F.M.[Fan-Man],
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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
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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
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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, Review
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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
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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
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Lv, K.F.[Ke-Feng],
Zhang, Y.S.[Yong-Sheng],
Yu, Y.[Ying],
Wang, H.Y.[Han-Yun],
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
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
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
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
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
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,
retrieval
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
Li, Y.J.[Yu-Jie],
Cai, J.T.[Jin-Tong],
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
Sun, S.Y.[Shu-Yang],
Yue, X.Y.[Xiao-Yu],
Zhao, H.S.[Heng-Shuang],
Torr, P.H.S.[Philip H.S.],
Bai, S.[Song],
Patch-Based Separable Transformer for Visual Recognition,
PAMI(45), No. 7, July 2023, pp. 9241-9247.
IEEE DOI
2306
Task analysis, Current transformers, Visualization,
Feature extraction, Convolutional neural networks,
instance segmentation
BibRef
Tang, X.Q.[Xiao-Qin],
Lv, L.P.[Ling-Peng],
Javanmardi, S.[Shima],
Wang, Y.F.[Yun-Feng],
Fan, J.C.[Jing-Chuan],
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.C.[Sheng-Chuan],
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
Mu, H.M.[Hong-Min],
Zhang, G.[Gang],
Ma, Z.[Zhe],
Zhou, M.C.[Meng-Chu],
Cao, Z.[Zhengcai],
Dynamic Obstacle Avoidance System Based on Rapid Instance
Segmentation Network,
ITS(25), No. 5, May 2024, pp. 4578-4592.
IEEE DOI
2405
Feature extraction, Task analysis, Collision avoidance, Real-time systems,
Distance measurement, Cameras, Semantics, indoor navigation
BibRef
Chen, J.P.[Jin-Peng],
Cong, R.M.[Run-Min],
Ip, H.H.S.[Horace Ho Shing],
Kwong, S.[Sam],
KepSalinst: Using Peripheral Points to Delineate Salient Instances,
Cyber(54), No. 6, June 2024, pp. 3392-3405.
IEEE DOI
2406
Task analysis, Head, Semantics, Object detection, Fuses, Urban areas,
Remote sensing, Dynamic convolution, peripheral points,
salient instance segmentation (SIS)
BibRef
Luo, Y.X.[Yu-Xuan],
Chen, J.P.[Jin-Peng],
Cong, R.M.[Run-Min],
Ip, H.H.S.[Horace Ho Shing],
Kwong, S.[Sam],
Trace Back and Go Ahead: Completing partial annotation for continual
semantic segmentation,
PR(165), 2025, pp. 111613.
Elsevier DOI
2505
Continual learning, Continual semantic segmentation, Replay-based
BibRef
Li, W.T.[Wen-Tong],
Liu, W.Y.[Wen-Yu],
Zhu, J.[Jianke],
Cui, M.M.[Miao-Miao],
Yu, R.S.[Ri-Sheng],
Hua, X.S.[Xian-Sheng],
Zhang, L.[Lei],
Box2Mask: Box-Supervised Instance Segmentation via Level-Set
Evolution,
PAMI(46), No. 7, July 2024, pp. 5157-5173.
IEEE DOI
2406
BibRef
Earlier: A1, A2, A3, A4, A6, A7, Only:
Box-Supervised Instance Segmentation with Level Set Evolution,
ECCV22(XXIX:1-18).
Springer DOI
2211
Instance segmentation, Annotations, Transformers,
Feature extraction, Training, Kernel, Image color analysis,
box supervision
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
Feng, C.[Chen],
Cheng, J.[Jian],
Xiao, Y.[Yang],
Cao, Z.G.[Zhi-Guo],
Advance One-Shot Multispectral Instance Detection With Text's
Supervision,
SPLetters(31), 2024, pp. 1605-1609.
IEEE DOI
2406
Feature extraction, Task analysis, Training, Visualization,
Representation learning, Semantics, Noise, multimodal feature learning
BibRef
Kanke, R.[Ryohei],
Takahashi, M.[Masanobu],
Amodal Instance Segmentation of Thin Objects with Large Overlaps by
Seed-to-Mask Extending,
IEICE(E108-D), No. 7, July 2024, pp. 908-911.
WWW Link.
2407
BibRef
Liu, S.Z.[Shuang-Zhou],
Wang, F.[Feng],
You, H.J.[Hong-Jian],
Jiao, N.G.[Nian-Gang],
Zhou, G.Y.[Guang-Yao],
Zhang, T.T.[Ting-Tao],
Context-Aggregated and SAM-Guided Network for ViT-Based Instance
Segmentation in Remote Sensing Images,
RS(16), No. 13, 2024, pp. 2472.
DOI Link
2407
BibRef
Wang, C.[Cheng],
Fang, Y.X.[Yu-Xin],
Fang, J.[Jiemin],
Guo, P.[Peng],
Wu, R.[Rui],
Huang, H.[He],
Wang, X.G.[Xing-Gang],
Huang, C.[Chang],
Liu, W.Y.[Wen-Yu],
Efficient Task-Specific Feature Re-Fusion for More Accurate Object
Detection and Instance Segmentation,
CirSysVideo(34), No. 7, July 2024, pp. 5350-5360.
IEEE DOI
2407
Task analysis, Feature extraction, Location awareness, Convolution,
Object detection, Detectors, Instance segmentation,
instance segmentation
BibRef
Liu, Y.[Yu],
Su, S.T.[Si-Tong],
Zhu, J.C.[Jun-Chen],
Zheng, F.[Feng],
Gao, L.L.[Lian-Li],
Song, J.K.[Jing-Kuan],
Allowing Supervision in Unsupervised Deformable- Instances
Image-to-Image Translation,
CirSysVideo(34), No. 7, July 2024, pp. 5335-5349.
IEEE DOI
2407
Task analysis, Training, Shape, Image synthesis, Image segmentation,
Generators, Deformation, Generative models,
image-to-image translation
BibRef
Peng, J.[Jin],
Wang, Y.X.[Yong-Xiong],
Pan, Z.Q.[Zhi-Qun],
Weakly supervised instance segmentation via class double-activation
maps and boundary localization,
SP:IC(127), 2024, pp. 117150.
Elsevier DOI
2408
Weakly supervised learning, Instance segmentation,
Class double-activation map (double-CAM), Boundary localization
BibRef
Ouyang, W.Z.[Wen-Zhe],
Xu, Z.L.[Zeng-Lin],
Xu, J.[Jing],
Wang, Q.F.[Qi-Fan],
Xu, Y.[Yong],
MixingMask: A contour-aware approach for joint object detection and
instance segmentation,
PR(155), 2024, pp. 110620.
Elsevier DOI
2408
Object detection, Instance segmentation, Vision perception,
Mixing, Contour regression
BibRef
Saidu, I.C.[Isah Charles],
Csató, L.[Lehel],
Deep multiple affinity model for proposal-free single instance
segmentation,
IJCVR(14), No. 5, 2024, pp. 491-509.
DOI Link
2409
BibRef
Yu, C.Y.[Cheng-Yan],
Zhang, D.[Dong],
Zou, W.[Wei],
Li, M.[Ming],
Joint Training on Multiple Datasets With Inconsistent Labeling
Criteria for Facial Expression Recognition,
AffCom(15), No. 3, July 2024, pp. 1812-1825.
IEEE DOI
2409
Training, Task analysis, Annotations, Face recognition, Multitasking,
Noise measurement, Standards, Deep convolutional neural networks,
continuous label mapping
BibRef
Deng, H.F.[Hong-Fei],
Wen, B.[Bin],
Wang, R.[Rui],
Feng, Z.[Zuwei],
Instance segmentation by blend U-Net and VOLO network,
IET-CV(18), No. 6, 2024, pp. 735-744.
DOI Link
2409
colouring, COT Encoder, instance segmentation, VOLO
BibRef
Feng, H.[Hao],
Zhou, K.[Keyi],
Zhou, W.G.[Wen-Gang],
Yin, Y.F.[Yu-Fei],
Deng, J.J.[Jia-Jun],
Sun, Q.[Qi],
Li, H.Q.[Hou-Qiang],
Recurrent Generic Contour-Based Instance Segmentation With
Progressive Learning,
CirSysVideo(34), No. 9, September 2024, pp. 7947-7961.
IEEE DOI Code:
WWW Link.
2410
Instance segmentation, Deformation, Task analysis, Shape,
Iterative methods, Text detection, lane detection
BibRef
Wang, H.[Huanan],
Zhang, X.Y.[Xin-Yu],
Wang, H.[Hong],
Jun, L.[Li],
Si-GAIS: Siamese Generalizable-Attention Instance Segmentation for
Intersection Perception System,
ITS(25), No. 11, November 2024, pp. 15759-15774.
IEEE DOI Code:
WWW Link.
2411
Instance segmentation, Cameras, IP networks, Accuracy,
Feature extraction, Task analysis, Laser radar,
intersection perception dataset
BibRef
Wu, Y.Z.[Yi-Zheng],
Pan, Z.Y.[Zhi-Yu],
Wang, K.W.[Ke-Wei],
Li, X.Y.[Xing-Yi],
Cui, J.H.[Jia-Hao],
Xiao, L.W.[Li-Wen],
Lin, G.S.[Guo-Sheng],
Cao, Z.G.[Zhi-Guo],
Instance Consistency Regularization for Semi-Supervised 3D Instance
Segmentation,
PAMI(46), No. 12, December 2024, pp. 9567-9582.
IEEE DOI
2411
Semantics, Instance segmentation, Kernel, Solid modeling,
Semisupervised learning, Semantic segmentation, 3D point clouds,
instance consistency regularization
BibRef
Han, Y.[Yue],
Zhang, J.N.[Jiang-Ning],
Wang, Y.[Yabiao],
Wang, C.J.[Cheng-Jie],
Liu, Y.[Yong],
Qi, L.[Lu],
Yang, M.H.[Ming-Hsuan],
Li, X.T.[Xiang-Tai],
Reference Twice: A Simple and Unified Baseline for Few-Shot Instance
Segmentation,
PAMI(46), No. 12, December 2024, pp. 9221-9238.
IEEE DOI
2411
Prototypes, Task analysis, Head, Feature extraction, Instance segmentation,
Transformers, Training, few-shot learning
BibRef
Wang, H.[Hai],
Qin, Q.[Qirui],
Chen, L.[Long],
Li, Y.C.[Yi-Cheng],
Cai, Y.F.[Ying-Feng],
RTMDet-MGG: A Multi-Task Model With Global Guidance,
ITS(25), No. 11, November 2024, pp. 16791-16804.
IEEE DOI
2411
Roads, Multitasking, Feature extraction, Task analysis,
Visualization, Instance segmentation, Convolution, Multi-task,
unstructured road
BibRef
Shanmugasundaram, S.[Suresh],
Palaniappan, N.[Natarajan],
Improvement of Bounding Box and Instance Segmentation Accuracy Using
ResNet-152 FPN with Modulated Deformable ConvNets v2 Backbone-based
Mask Scoring R-CNN,
IJIG(24), No. 6, November 2024, pp. 2450054.
DOI Link
2501
BibRef
Xu, J.T.[Jing-Ting],
Luo, P.[Peng],
Mu, D.J.[De-Jun],
Weakly Supervised Instance Segmentation in Aerial Images via
Comprehensive Spatial Adaptation,
RS(16), No. 24, 2024, pp. 4757.
DOI Link
2501
BibRef
Jang, J.[Jaeseok],
Kim, D.[Dahyun],
Jin, D.[Dongkwon],
Kim, C.S.[Chang-Su],
Contour-based object forecasting for autonomous driving,
JVCIR(106), 2025, pp. 104343.
Elsevier DOI
2501
Instance segmentation, Depth estimation,
Contour representation, Segmentation forecasting, Depth forecasting
BibRef
Xie, J.H.[Jia-Hao],
Li, W.[Wei],
Liu, Z.W.[Zi-Wei],
Ong, Y.S.[Yew Soon],
Loy, C.C.[Chen Change],
MosaicFusion: Diffusion Models as Data Augmenters for Large Vocabulary
Instance Segmentation,
IJCV(133), No. 4, April 2025, pp. 1456-1475.
Springer DOI
2504
BibRef
Yang, Y.F.[Yun-Fei],
Deng, H.W.[Hong-Wei],
Wu, Y.C.[Yi-Chun],
MFC-Net: Amodal instance segmentation with multi-path fusion and
context-awareness,
IVC(158), 2025, pp. 105539.
Elsevier DOI
2505
MFC-net, Transformer, Feature fusion, Amodal instance segmentation
BibRef
Liu, X.Y.[Xiao-Yu],
Zhang, Y.[Yueyi],
Xiong, Z.W.[Zhi-Wei],
Huang, W.[Wei],
Hu, B.[Bo],
Sun, X.Y.[Xiao-Yan],
Wu, F.[Feng],
Graph relation distillation for efficient biomedical instance
segmentation,
PR(167), 2025, pp. 111748.
Elsevier DOI Code:
WWW Link.
2506
Biomedical instance segmentation, Pixel embeddings, Knowledge distillation
BibRef
Tschirschwitz, D.[David],
Rodehorst, V.[Volker],
Label Convergence: Defining an Upper Performance Bound in Object
Recognition Through Contradictory Annotations,
WACV25(6848-6857)
IEEE DOI
2505
Training, Analytical models, Upper bound, Annotations, Noise,
Object detection, Data models, Object recognition, Convergence,
instance segmentation
BibRef
Chen, J.[Jun],
Khan, F.F.[Faizan Farooq],
Hu, M.[Ming],
Sherif, A.[Ammar],
Ge, Z.Y.[Zong-Yuan],
Li, B.Y.[Bo-Yang],
Elhoseiny, M.[Mohamed],
Local Masked Reconstruction for Efficient Self-Supervised Learning on
High-Resolution Images,
WACV25(8046-8056)
IEEE DOI Code:
WWW Link.
2505
Instance segmentation, Accuracy, Semantic segmentation,
Computational modeling, Self-supervised learning, efficient training
BibRef
Munir, M.[Mustafa],
Rahman, M.M.[Md Mostafijur],
Marculescu, R.[Radu],
RapidNet: Multi-Level Dilated Convolution Based Mobile Backbone,
WACV25(8302-8312)
IEEE DOI Code:
WWW Link.
2505
Instance segmentation, Accuracy, Computational modeling,
Semantic segmentation, Object detection, mobile ai
BibRef
Patro, B.N.[Badri N.],
Namboodiri, V.P.[Vinay P.],
Agneeswaran, V.S.[Vijay S.],
SpectFormer: Frequency and Attention is what you need in a Vision
Transformer,
WACV25(9543-9554)
IEEE DOI Code:
WWW Link.
2505
Instance segmentation, Accuracy, Source coding, Image edge detection,
Transfer learning, Object detection, transformer
BibRef
Tran, M.[Minh],
Vo, K.[Khoa],
Nguyen, T.[Tri],
Le, N.[Ngan],
Amodal Instance Segmentation with Diffusion Shape Prior Estimation,
ACCV24(X: 309-324).
Springer DOI
2412
BibRef
Li, D.[Dylan],
Shin, G.[Gyungin],
Promerge: Prompt and Merge for Unsupervised Instance Segmentation,
ECCV24(XIV: 1-17).
Springer DOI
2412
BibRef
Huang, P.H.[Po-Hsuan],
Lin, C.C.[Chia-Ching],
Hsu, C.F.[Chih-Fan],
Chang, M.C.[Ming-Ching],
Chen, W.C.[Wei-Chao],
Learning With Instance-Dependent Noisy Labels By Anchor Hallucination
And Hard Sample Label Correction,
ICIP24(901-907)
IEEE DOI
2411
Training, Visualization, Noise, Training data, Robustness,
Noise measurement, Noisy-label learning, semi-supervised learning
BibRef
Chen, Z.W.[Zhi-Wen],
Wu, W.[Wei],
Chen, Z.[Zhengfeng],
Learning A Rain-Invariant Network For Instance Segmentation In The
Rain,
ICIP24(2578-2584)
IEEE DOI
2411
Instance segmentation, Degradation, Adaptation models,
Adaptive learning, Rain, Pipelines, Feature extraction, rainy dataset
BibRef
Zhang, Z.[Zifu],
Li, S.X.[Sheng-Xi],
Liu, T.[Tie],
Xu, M.[Mai],
Xu, T.[Tao],
Guan, Z.Y.[Zhen-Yu],
Lv, Z.Y.[Zhuo-Yi],
Hybrid Single Input and Multiple Output Method For Compressing
Features Towards Machine Vision Tasks,
ICIP24(1870-1876)
IEEE DOI
2411
Video coding, Instance segmentation, Training, Image coding,
Machine vision, Termination of employment, Transform coding,
image compression
BibRef
Mais, L.[Lisa],
Hirsch, P.[Peter],
Managan, C.[Claire],
Kandarpa, R.[Ramya],
Rumberger, J.L.[Josef Lorenz],
Reinke, A.[Annika],
Maier-Hein, L.[Lena],
Ihrke, G.[Gudrun],
Kainmueller, D.[Dagmar],
FISBe: A Real-World Benchmark Dataset for Instance Segmentation of
Long-Range thin Filamentous Structures,
CVPR24(22249-22259)
IEEE DOI Code:
WWW Link.
2410
Instance segmentation, Measurement, Neuroscience,
Image color analysis, Annotations, Microscopy,
3D Light Microscopy
BibRef
Wang, K.L.[Ke-Lei],
Chou, P.H.[Pin-Hsuan],
Chou, Y.C.[Young-Ching],
Liu, C.J.[Chia-Jen],
Lin, C.K.[Cheng-Kuan],
Tseng, Y.C.[Yu-Chee],
MP-PolarMask: A Faster and Finer Instance Segmentation for Concave
Images,
MTF24(3705-3714)
IEEE DOI
2410
Instance segmentation, Accuracy, Shape, Real-time systems,
Deep learning, Instance segmentation,
Multi-point PolarMask
BibRef
Chen, T.W.[Tse-Wei],
Tao, W.[Wei],
Zhao, D.[Dongyue],
Mima, K.[Kazuhiro],
Ito, T.[Tadayuki],
Osa, K.[Kinya],
Kato, M.[Masami],
Dedicated Inference Engine and Binary-Weight Neural Networks for
Lightweight Instance Segmentation,
ECVW24(2101-2110)
IEEE DOI
2410
Instance segmentation, Costs, Accuracy, Design methodology,
Neural networks, Logic gates
BibRef
Das, A.M.[Arnav M.],
Chaudhry, R.[Ritwick],
Kundu, K.[Kaustav],
Modolo, D.[Davide],
Prompting Foundational Models for Omni-supervised Instance
Segmentation,
Prompting24(1583-1592)
IEEE DOI
2410
Instance segmentation, Training, Costs, Annotations, Computational modeling
BibRef
Xiang, J.Y.[Jing-Yang],
Li, S.Q.[Si-Qi],
Chen, J.H.[Jun-Hao],
Chen, Z.Z.[Zhuang-Zhi],
Huang, T.X.[Tian-Xin],
Peng, L.P.[Lin-Peng],
Liu, Y.[Yong],
MaxQ: Multi-Axis Query for N:m Sparsity Network,
CVPR24(15845-15854)
IEEE DOI Code:
WWW Link.
2410
Training, Instance segmentation, Schedules, Runtime, Object detection,
Performance gain, Distortion, N:M sparsity, relative importance
BibRef
Moon, J.[Jaehyeon],
Kim, D.[Dohyung],
Cheon, J.Y.[Jun-Yong],
Ham, B.[Bumsub],
Instance-Aware Group Quantization for Vision Transformers,
CVPR24(16132-16141)
IEEE DOI
2410
Instance segmentation, Quantization (signal), Neural networks,
Object detection, Predictive models, ViT,
Post-training quantization
BibRef
Lee, H.[Hyeonjun],
Hwang, S.[Sehyun],
Kwak, S.[Suha],
Extreme Point Supervised Instance Segmentation,
CVPR24(17212-17222)
IEEE DOI
2410
Instance segmentation, Training, Costs, Annotations,
Supervised learning, Benchmark testing, instance segmentation, extreme point
BibRef
Zou, B.[Bo],
Wang, S.F.[Shao-Feng],
Liu, H.[Hao],
Sun, G.[Gaoyue],
Wang, Y.J.[Ya-Jie],
Zuo, F.[FeiFei],
Quan, C.B.[Cheng-Bin],
Zhao, Y.J.[You-Jian],
Teeth-SEG: An Efficient Instance Segmentation Framework for
Orthodontic Treatment Based on Multi-Scale Aggregation and Anthropic
Prior Knowledge,
CVPR24(11601-11610)
IEEE DOI
2410
Instance segmentation, Location awareness, Visualization, Shape,
Computational modeling, Semantics, Teeth, Medical Vision,
Teeth Segmentation
BibRef
Tian, X.[Xin],
Xu, K.[Ke],
Lau, R.[Rynson],
Unsupervised Salient Instance Detection,
CVPR24(2702-2712)
IEEE DOI
2410
Adaptation models, Visualization, Computational modeling,
Coherence, Manuals, Feature extraction
BibRef
Wei, Z.Y.[Zhao-Yang],
Chen, P.F.[Peng-Fei],
Yu, X.[Xuehui],
Li, G.R.[Guo-Rong],
Jia, J.B.[Jian-Bin],
Han, Z.J.[Zhen-Jun],
Semantic-aware SAM for Point-Prompted Instance Segmentation,
CVPR24(3585-3594)
IEEE DOI Code:
WWW Link.
2410
Instance segmentation, Visualization, Electric potential, Costs,
Annotations, Semantics, Transforms, Semantic Ambiguity,
Point Prompted Instance Segmentation
BibRef
Kara, S.[Sandra],
Ammar, H.[Hejer],
Denize, J.[Julien],
Chabot, F.[Florian],
Pham, Q.C.[Quoc-Cuong],
DIOD: Self-Distillation Meets Object Discovery,
CVPR24(3975-3985)
IEEE DOI Code:
WWW Link.
2410
Instance segmentation, Training, Accuracy, Motion segmentation, Noise,
Object discovery, self-distillation, Unsupervised learning
BibRef
Fan, C.X.[Cheng-Xiang],
Zhu, M.[Muzhi],
Chen, H.[Hao],
Liu, Y.[Yang],
Wu, W.J.[Wei-Jia],
Zhang, H.Q.[Hua-Qi],
Shen, C.H.[Chun-Hua],
DiverGen: Improving Instance Segmentation by Learning Wider Data
Distribution with More Diverse Generative Data,
CVPR24(3986-3995)
IEEE DOI Code:
WWW Link.
2410
Instance segmentation, Training, Measurement, Annotations, Pipelines,
Data augmentation, instance segmentation,
generative data augmentation
BibRef
Shang, C.[Chao],
Song, Z.C.[Zi-Chen],
Qiu, H.Q.[He-Qian],
Wang, L.X.[Lan-Xiao],
Meng, F.M.[Fan-Man],
Li, H.L.[Hong-Liang],
Prompt-Driven Referring Image Segmentation with Instance Contrasting,
CVPR24(4124-4134)
IEEE DOI
2410
Bridges, Image segmentation, Adaptation models, Accuracy,
Computational modeling, Natural languages, prompt learning
BibRef
Fan, Q.H.[Qi-Hang],
Huang, H.B.[Huai-Bo],
Chen, M.R.[Ming-Rui],
Liu, H.M.[Hong-Min],
He, R.[Ran],
RMT: Retentive Networks Meet Vision Transformers,
CVPR24(5641-5651)
IEEE DOI
2410
Instance segmentation, Computational modeling, Training data,
Object detection, Transformer cores, Transformers, Vision Transformer
BibRef
Munir, M.[Mustafa],
Avery, W.[William],
Rahman, M.M.[Md Mostafijur],
Marculescu, R.[Radu],
GreedyViG: Dynamic Axial Graph Construction for Efficient Vision GNNs,
CVPR24(6118-6127)
IEEE DOI Code:
WWW Link.
2410
Instance segmentation, Accuracy, Computational modeling,
Semantic segmentation, Object detection,
Graph Neural Networks
BibRef
Wang, X.D.[Xu-Dong],
Darrell, T.J.[Trevor J.],
Rambhatla, S.S.[Sai Saketh],
Girdhar, R.[Rohit],
Misra, I.[Ishan],
InstanceDiffusion: Instance-Level Control for Image Generation,
CVPR24(6232-6242)
IEEE DOI
2410
Instance segmentation, Image synthesis, Computational modeling,
Text to image, Diffusion models, Pattern recognition
BibRef
Jodogne-del Litto, K.[Katia],
Bilodeau, G.A.[Guillaume-Alexandre],
Real-Time Instance Segmentation with Polygons Using an
Intersection-Over-Union Loss,
CRV23(153-160)
IEEE DOI Code:
WWW Link.
2406
Training, Image segmentation, Head, Protocols, Codes, Robot kinematics,
Roads, instance segmentation, intersection-over-union, urban scene,
mask approximation
BibRef
Liu, K.[Keyi],
Elder, J.H.[James H.],
Sparse Shape Encoding for Topologically Improved Instance
Segmentation,
CRV23(45-54)
IEEE DOI
2406
Visualization, Shape, Level set, Neurons, Transforms,
Benchmark testing, Instance Segmentation, Sparse Shape Encoding,
Convolutional Neural Networks
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,
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
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
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.M.[Run-Min],
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.Y.[Zi-Yun],
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
Su, J.M.[Jin-Ming],
Yin, R.H.[Rui-Hong],
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
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
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
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
Boyadzhiev, T.[Teodor],
Ivanova, K.[Krassimira],
Instance Segmentation with BoundaryNet,
IWCIA22(260-269).
Springer DOI
2301
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
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.Z.[Hui-Zhong],
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
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
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,
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,
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,
Transformers, Segmentation,
Deep learning architectures and techniques
BibRef
Zhu, C.M.[Chen-Ming],
Zhang, X.Y.[Xuan-Ye],
Li, Y.R.[Yan-Ran],
Qiu, L.D.[Liang-Dong],
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, 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,
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, retrieval
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, 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,
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
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,
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
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,
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,
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, 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
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,
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, 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
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
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
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,
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,
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
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
Zhang, Y.[Yi],
Guo, M.H.[Meng-Hao],
Wang, M.[Miao],
Hu, S.M.[Shi-Min],
Exploring Regional Clues in CLIP for Zero-Shot Semantic Segmentation,
CVPR24(3270-3280)
IEEE DOI Code:
WWW Link.
2410
Training, Bridges, Visualization, Image recognition, Codes,
Semantic segmentation, zero-shot semantic segmentation, semantic segmentation
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
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
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
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
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
semant
Chapter on 2-D Region Segmentation Techniques, Snakes, Active Contours continues in
Single-Shot, Few-Shot Instance Segmentation .