8.6.2 Semantic Segmentation, Label and Segment Together

Zheng, C.[Chen], Zhang, Y.[Yun], Wang, L.G.[Lei-Guang],
Semantic Segmentation of Remote Sensing Imagery Using an Object-Based Markov Random Field Model With Auxiliary Label Fields,
GeoRS(55), No. 5, May 2017, pp. 3015-3028.
IEEE DOI 1705
Markov processes, image segmentation, remote sensing, auxiliary label field, hierarchical semantic information, object-based MRF model, object-based Markov random field model, probability distribution, remote sensing imagery, remote sensing images, semantic segmentation, Context, Context modeling, Image segmentation, Probability distribution, Remote sensing, Semantics, Spatial resolution, Auxiliary label field, object-based Markov random field, remote sensing image, semantic, segmentation BibRef

Liu, Y.[Yu], Nguyen, D.M.[Duc Minh], Deligiannis, N.[Nikos], Ding, W.[Wenrui], Munteanu, A.[Adrian],
Hourglass-Shape Network Based Semantic Segmentation for High Resolution Aerial Imagery,
RS(9), No. 6, 2017, pp. xx-yy.
DOI Link 1706
BibRef

Czúni, L.[László], Rashad, M.[Metwally],
The use of IMUs for video object retrieval in lightweight devices,
JVCIR(48), No. 1, 2017, pp. 30-42.
Elsevier DOI 1708
BibRef
Earlier:
View centered video-based object recognition for lightweight devices,
WSSIP16(1-4)
IEEE DOI 1608
Video object retrieval. image recognition BibRef

Czuni, L.[Laszlo], Kiss, P.J.[Peter Jozsef], Lipovits, A.[Agnes], Gal, M.[Monika],
Lightweight mobile object recognition,
ICIP14(3426-3428)
IEEE DOI 1502
Cameras CEDD (Color and Edge Directivity Descriptor). BibRef

Badrinarayanan, V.[Vijay], Kendall, A.[Alex], Cipolla, R.[Roberto],
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation,
PAMI(39), No. 12, December 2017, pp. 2481-2495.
IEEE DOI 1711
Convolutional codes, Decoding, Image segmentation, Neural networks, Semantics, Training, indoor scenes, pooling, road scenes, semantic pixel-wise segmentation, upsampling BibRef

Marmanis, D., Schindler, K., Wegner, J.D., Galliani, S., Datcu, M., Stilla, U.,
Classification with an edge: Improving semantic image segmentation with boundary detection,
PandRS(135), No. Supplement C, 2018, pp. 158-172.
Elsevier DOI 1712
BibRef

Arnab, A.[Anurag], Zheng, S.[Shuai], Jayasumana, S.[Sadeep], Romera-Paredes, B.[Bernardino], Larsson, M., Kirillov, A., Savchynskyy, B., Rother, C., Kahl, F., Torr, P.H.S.[Philip H. S.],
Conditional Random Fields Meet Deep Neural Networks for Semantic Segmentation: Combining Probabilistic Graphical Models with Deep Learning for Structured Prediction,
SPMag(35), No. 1, January 2018, pp. 37-52.
IEEE DOI 1801
Computational modeling, Computer vision, Feature extraction, Image segmentation, Semantics, Visualization BibRef

Arnab, A.[Anurag], Jayasumana, S.[Sadeep], Zheng, S.[Shuai], Torr, P.H.S.[Philip H. S.],
Higher Order Conditional Random Fields in Deep Neural Networks,
ECCV16(II: 524-540).
Springer DOI 1611
BibRef

Arnab, A.[Anurag], Torr, P.H.S.[Philip H. S.],
Pixelwise Instance Segmentation with a Dynamically Instantiated Network,
CVPR17(879-888)
IEEE DOI 1711
Detectors, Image segmentation, Object detection, Pipelines, Proposals, Semantics. First, semantic segmentation, then object instance detection. BibRef

Arnab, A.[Anurag], Torr, P.H.S.[Philip H.S.],
Bottom-up Instance Segmentation using Deep Higher-Order CRFs,
BMVC16(xx-yy).
HTML Version. 1805
BibRef

Zheng, S.[Shuai], Jayasumana, S.[Sadeep], Romera-Paredes, B.[Bernardino], Vineet, V.[Vibhav], Su, Z.Z.[Zhi-Zhong], Du, D.L.[Da-Long], Huang, C.[Chang], Torr, P.H.S.[Philip H. S.],
Conditional Random Fields as Recurrent Neural Networks,
ICCV15(1529-1537)
IEEE DOI 1602
Combine CNN with CRF. BibRef

Larsson, M.[Måns], Alvén, J.[Jennifer], Kahl, F.[Fredrik],
Max-Margin Learning of Deep Structured Models for Semantic Segmentation,
SCIA17(II: 28-40).
Springer DOI 1706
BibRef

Saleh, F.S.[Fatemehsadat S.], Aliakbarian, M.S.[Mohammad Sadegh], Salzmann, M.[Mathieu], Petersson, L.[Lars], Alvarez, J.M.[Jose M.], Gould, S.[Stephen],
Incorporating Network Built-in Priors in Weakly-Supervised Semantic Segmentation,
PAMI(40), No. 6, June 2018, pp. 1382-1396.
IEEE DOI 1805
BibRef
Earlier: A1, A2, A3, A4, A6, A5:
Built-in Foreground/Background Prior for Weakly-Supervised Semantic Segmentation,
ECCV16(VIII: 413-432).
Springer DOI 1611
Data mining, Image segmentation, Machine learning, Neural networks, Object recognition, Semantics, Training, Semantic segmentation, weakly-supervised semantic segmentation BibRef

Saleh, F.S.[Fatemehsadat S.], Aliakbarian, M.S.[Mohammad Sadegh], Salzmann, M.[Mathieu], Petersson, L.[Lars], Alvarez, J.M.[Jose M.],
Bringing Background into the Foreground: Making All Classes Equal in Weakly-Supervised Video Semantic Segmentation,
ICCV17(2125-2135)
IEEE DOI 1802
image classification, image segmentation, learning (artificial intelligence), video signal processing, Semantics BibRef

Lin, G., Shen, C., van den Hengel, A.J.[Anton J.], Reid, I.D.,
Exploring Context with Deep Structured Models for Semantic Segmentation,
PAMI(40), No. 6, June 2018, pp. 1352-1366.
IEEE DOI 1805
BibRef
Earlier:
Efficient Piecewise Training of Deep Structured Models for Semantic Segmentation,
CVPR16(3194-3203)
IEEE DOI 1612
Context, Context modeling, Image resolution, Image segmentation, Neural networks, Semantics, Training, Semantic segmentation, convolutional neural networks BibRef

Lin, G., Milan, A., Shen, C., Reid, I.D.,
RefineNet: Multi-path Refinement Networks for High-Resolution Semantic Segmentation,
CVPR17(5168-5177)
IEEE DOI 1711
Computer architecture, Convolution, Image resolution, Image segmentation, Semantics, Training BibRef

Zhang, Y.[Yu], Chen, X.W.[Xiao-Wu], Li, J.[Jia], Wang, C.[Chen], Xia, C.Q.[Chang-Qun], Li, J.[Jun],
Semantic Object Segmentation in Tagged Videos via Detection,
PAMI(40), No. 7, July 2018, pp. 1741-1754.
IEEE DOI 1806
Image segmentation, Motion segmentation, Object segmentation, Proposals, Semantics, Spatiotemporal phenomena, Videos, weakly supervised segmentation BibRef

Zhang, Y.[Yu], Chen, X.W.[Xiao-Wu], Li, J.[Jia], Teng, W.[Wei], Song, H.[Haokun],
Exploring Weakly Labeled Images for Video Object Segmentation With Submodular Proposal Selection,
IP(27), No. 9, September 2018, pp. 4245-4259.
IEEE DOI 1807
computer vision, data mining, image matching, image segmentation, learning (artificial intelligence), video signal processing, weakly labeled video BibRef

Zhang, Y.[Yu], Chen, X.W.[Xiao-Wu], Li, J.[Jia], Wang, C.[Chen], Xia, C.Q.[Chang-Qun],
Semantic object segmentation via detection in weakly labeled video,
CVPR15(3641-3649)
IEEE DOI 1510
BibRef

Zhang, J.[Jing], Mu, Y.[Yakun], Feng, S.W.[Sheng-Wei], Li, K.H.[Ke-Huang], Yuan, Y.[Yubo], Lee, C.H.[Chin-Hui],
Image region annotation based on segmentation and semantic correlation analysis,
IET-IPR(12), No. 8, August 2018, pp. 1331-1337.
DOI Link 1808
BibRef

Volpi, M.[Michele], Tuia, D.[Devis],
Deep multi-task learning for a geographically-regularized semantic segmentation of aerial images,
PandRS(144), 2018, pp. 48-60.
Elsevier DOI 1809
Semantic segmentation, Semantic boundary detection, Convolutional neural networks, Conditional random fields, Aerial imagery BibRef

Shi, H., Li, H., Meng, F., Wu, Q., Xu, L., Ngan, K.N.,
Hierarchical Parsing Net: Semantic Scene Parsing From Global Scene to Objects,
MultMed(20), No. 10, October 2018, pp. 2670-2682.
IEEE DOI 1810
backpropagation, feature extraction, image classification, image coding, local appearance features, contextual feature, context learning BibRef

Noormohamadi, N.[Neda], Adibi, P.[Peyman], Ehsani, S.M.S.[Sayyed Mohammad Saeed],
Semantic image segmentation using an improved hierarchical graphical model,
IET-IPR(12), No. 11, November 2018, pp. 1943-1950.
DOI Link 1810
BibRef

Yu, C.Q.[Chang-Qian], Wang, J.B.[Jing-Bo], Peng, C.[Chao], Gao, C.X.[Chang-Xin], Yu, G.[Gang], Sang, N.[Nong],
BiSeNet: Bilateral Segmentation Network for Real-Time Semantic Segmentation,
ECCV18(XIII: 334-349).
Springer DOI 1810
BibRef

Huang, P.Y.[Po-Yu], Hsu, W.T.[Wan-Ting], Chiu, C.Y.[Chun-Yueh], Wu, T.F.[Ting-Fan], Sun, M.[Min],
Efficient Uncertainty Estimation for Semantic Segmentation in Videos,
ECCV18(I: 536-552).
Springer DOI 1810
BibRef

Ke, T.W.[Tsung-Wei], Hwang, J.J.[Jyh-Jing], Liu, Z.[Ziwei], Yu, S.X.[Stella X.],
Adaptive Affinity Fields for Semantic Segmentation,
ECCV18(I: 605-621).
Springer DOI 1810
BibRef

Zhao, H.[Hengshuang], Qi, X.J.[Xiao-Juan], Shen, X.Y.[Xiao-Yong], Shi, J.P.[Jian-Ping], Jia, J.Y.[Jia-Ya],
ICNet for Real-Time Semantic Segmentation on High-Resolution Images,
ECCV18(III: 418-434).
Springer DOI 1810
BibRef

Lin, D.[Di], Ji, Y.[Yuanfeng], Lischinski, D.[Dani], Cohen-Or, D.[Daniel], Huang, H.[Hui],
Multi-scale Context Intertwining for Semantic Segmentation,
ECCV18(III: 622-638).
Springer DOI 1810
BibRef

Zou, Y.[Yang], Yu, Z.D.[Zhi-Ding], Kumar, B.V.K.V.[B. V. K. Vijaya], Wang, J.S.[Jin-Song],
Unsupervised Domain Adaptation for Semantic Segmentation via Class-Balanced Self-training,
ECCV18(III: 297-313).
Springer DOI 1810
BibRef

Baslamisli, A.S.[Anil S.], Groenestege, T.T.[Thomas T.], Das, P.[Partha], Le, H.A.[Hoang-An], Karaoglu, S.[Sezer], Gevers, T.[Theo],
Joint Learning of Intrinsic Images and Semantic Segmentation,
ECCV18(VI: 289-305).
Springer DOI 1810
BibRef

Zhu, X.[Xinge], Zhou, H.[Hui], Yang, C.[Ceyuan], Shi, J.P.[Jian-Ping], Lin, D.[Dahua],
Penalizing Top Performers: Conservative Loss for Semantic Segmentation Adaptation,
ECCV18(VII: 587-603).
Springer DOI 1810
BibRef

Fan, R.C.[Ruo-Chen], Hou, Q.[Qibin], 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

Zhang, Z.Y.[Zhen-Yu], Cui, Z.[Zhen], Xu, C.Y.[Chun-Yan], Jie, Z.Q.[Ze-Qun], Li, X.[Xiang], Yang, J.[Jian],
Joint Task-Recursive Learning for Semantic Segmentation and Depth Estimation,
ECCV18(X: 238-255).
Springer DOI 1810
BibRef

Dai, A.[Angela], Nießner, M.[Matthias],
3DMV: Joint 3D-Multi-view Prediction for 3D Semantic Scene Segmentation,
ECCV18(X: 458-474).
Springer DOI 1810
BibRef

Mehta, S.[Sachin], Rastegari, M.[Mohammad], Caspi, A.[Anat], Shapiro, L.[Linda], Hajishirzi, H.[Hannaneh],
ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation,
ECCV18(X: 561-580).
Springer DOI 1810
BibRef

Xiao, C.W.[Chao-Wei], Deng, R.Z.[Rui-Zhi], Li, B.[Bo], Yu, F.[Fisher], Liu, M.Y.[Ming-Yan], Song, D.[Dawn],
Characterizing Adversarial Examples Based on Spatial Consistency Information for Semantic Segmentation,
ECCV18(X: 220-237).
Springer DOI 1810
BibRef

Zhang, Z.L.[Zhen-Li], Zhang, X.Y.[Xiang-Yu], Peng, C.[Chao], Xue, X.Y.[Xiang-Yang], Sun, J.[Jian],
ExFuse: Enhancing Feature Fusion for Semantic Segmentation,
ECCV18(X: 273-288).
Springer DOI 1810
BibRef

Sulimowicz, L., Ahmad, I., Aved, A.,
Superpixel-Enhanced Pairwise Conditional Random Field for Semantic Segmentation,
ICIP18(271-275)
IEEE DOI 1809
Image segmentation, Semantics, Kernel, Labeling, Robustness, Visualization, Image color analysis, and Higher-order CRFs BibRef

Lu, L.H.[Li-Hsien], Hsu, C.T.[Chiou-Ting],
Semantic Segmentation for Real-World Data by Jointly Exploiting Supervised andxs Transferrable Knowledge,
BMVC16(xx-yy).
HTML Version. 1805
BibRef

Chaurasia, A., Culurciello, E.,
LinkNet: Exploiting encoder representations for efficient semantic segmentation,
VCIP17(1-4)
IEEE DOI 1804
computer vision, image resolution, image segmentation, learning (artificial intelligence), neural nets, LinkNet, Training BibRef

Wilhelm, T., Grzeszick, R., Fink, G.A., Woehler, C.,
From Weakly Supervised Object Localization to Semantic Segmentation by Probabilistic Image Modeling,
DICTA17(1-7)
IEEE DOI 1804
image segmentation, learning (artificial intelligence), object detection, convolutional network, deep learning, Training BibRef

Zhang, Y., Ngan, K.N., Huynh, C.P., Habili, N.,
Learning Deep Spatial-Spectral Features for Material Segmentation in Hyperspectral Images,
DICTA17(1-7)
IEEE DOI 1804
feature extraction, geophysical image processing, image classification, image segmentation, Training BibRef

Cui, Z., Zhang, Q., Geng, S., Niu, X., Yang, J., Qiao, Y.,
Semantic segmentation with multi-path refinement and pyramid pooling dilated-resnet,
ICIP17(3100-3104)
IEEE DOI 1803
Computer architecture, Convolution, Feature extraction, Image segmentation, Semantics, Task analysis, Training, Segmentation BibRef

Xie, C., Wang, J., Zhang, Z., Zhou, Y., Xie, L., Yuille, A.L.[Alan L.],
Adversarial Examples for Semantic Segmentation and Object Detection,
ICCV17(1378-1387)
IEEE DOI 1802
image classification, image segmentation, object detection, pattern clustering, adversarial perturbations, Semantics BibRef

Zhang, Y., David, P., Gong, B.,
Curriculum Domain Adaptation for Semantic Segmentation of Urban Scenes,
ICCV17(2039-2049)
IEEE DOI 1802
computer graphics, convolution, image classification, image segmentation, learning (artificial intelligence), Training BibRef

Luc, P.[Pauline], Couprie, C.[Camille], Le Cun, Y.[Yann], 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.[Yann],
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

Peng, C., Zhang, X., Yu, G., Luo, G., Sun, J.,
Large Kernel Matters: Improve Semantic Segmentation by Global Convolutional Network,
CVPR17(1743-1751)
IEEE DOI 1711
Computational modeling, Feature extraction, Image segmentation, Kernel, Semantics, Standards BibRef

Zhu, Y., Tian, Y., Metaxas, D., Dollár, P.,
Semantic Amodal Segmentation,
CVPR17(3001-3009)
IEEE DOI 1711
Image edge detection, Image segmentation, Object detection, Semantics, Tools, Visualization BibRef

Vernaza, P., Chandraker, M.,
Learning Random-Walk Label Propagation for Weakly-Supervised Semantic Segmentation,
CVPR17(2953-2961)
IEEE DOI 1711
Image edge detection, Image segmentation, Labeling, Semantics, Training, Uncertainty BibRef

Pohlen, T., Hermans, A.[Alexander], Mathias, M., Leibe, B.[Bastian],
Full-Resolution Residual Networks for Semantic Segmentation in Street Scenes,
CVPR17(3309-3318)
IEEE DOI 1711
Computer architecture, Image segmentation, Network architecture, Semantics, Streaming media, 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

Shen, F., Gan, R., Yan, S., Zeng, G.,
Semantic Segmentation via Structured Patch Prediction, Context CRF and Guidance CRF,
CVPR17(5178-5186)
IEEE DOI 1711
Complexity theory, Image segmentation, Message passing, Predictive models, Semantics, Training BibRef

Luo, P.[Ping], Wang, G.R.[Guang-Run], Lin, L.[Liang], Wang, X.G.[Xiao-Gang],
Deep Dual Learning for Semantic Image Segmentation,
ICCV17(2737-2745)
IEEE DOI 1802
BibRef
Earlier: A2, A1, A3, A4:
Learning Object Interactions and Descriptions for Semantic Image Segmentation,
CVPR17(5235-5243)
IEEE DOI 1711
image reconstruction, image segmentation, learning (artificial intelligence), neural nets, DIS, Cleaning, Cows, Feature extraction, Image segmentation, Semantics, Streaming media. BibRef

Wigness, M., Rogers, J.G.,
Unsupervised Semantic Scene Labeling for Streaming Data,
CVPR17(5910-5919)
IEEE DOI 1711
Adaptation models, Data models, Image segmentation, Labeling, Semantics, Streaming media, Visualization BibRef

Bulò, S.R., Neuhold, G., Kontschieder, P.,
Loss Max-Pooling for Semantic Image Segmentation,
CVPR17(7082-7091)
IEEE DOI 1711
Benchmark testing, Image segmentation, Semantics, Standards, Training, Upper, bound BibRef

He, Y.[Yang], Keuper, M.[Margret], Schiele, B.[Bernt], Fritz, M.[Mario],
Learning Dilation Factors for Semantic Segmentation of Street Scenes,
GCPR17(41-51).
Springer DOI 1711
BibRef

He, Y.[Yang], Chiu, W.C., Keuper, M.[Margret], Fritz, M.[Mario],
STD2P: RGBD Semantic Segmentation Using Spatio-Temporal Data-Driven Pooling,
CVPR17(7158-7167)
IEEE DOI 1711
Image segmentation, Indexes, Optical imaging, Semantics, Training, Videos BibRef

Jégou, S.[Simon], Drozdzal, M.[Michal], Vazquez, D.[David], Romero, A.[Adriana], Bengio, Y.[Yoshua],
The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation,
CVVT17(1175-1183)
IEEE DOI 1709
Benchmark testing, Computer architecture, Image segmentation, Semantics, Spatial resolution, Standards BibRef

Derue, F.X.[François-Xavier], Dahmane, M.[Mohamed], Lalonde, M.[Marc], Foucher, S.[Samuel],
Exploiting Semantic Segmentation for Robust Camera Motion Classification,
ICIAR17(173-181).
Springer DOI 1706
BibRef

Namin, S.R., Alvarez, J.M., Petersson, L.,
2D-3D semantic segmentation using cardinality as higher-order loss,
ICPR16(3775-3780)
IEEE DOI 1705
Image edge detection, Image segmentation, Labeling, Sensors, Three-dimensional displays, Training, Two, dimensional, displays BibRef

Wang, H.L.[Hui-Ling], Raiko, T.[Tapani], Lensu, L.[Lasse], Wang, T.H.[Ting-Huai], Karhunen, J.[Juha],
Semi-supervised Domain Adaptation for Weakly Labeled Semantic Video Object Segmentation,
ACCV16(I: 163-179).
Springer DOI 1704
BibRef

Audebert, N.[Nicolas], Le Saux, B.[Bertrand], Lefèvre, S.[Sébastien],
Joint Learning from Earth Observation and OpenStreetMap Data to Get Faster Better Semantic Maps,
EarthVision17(1552-1560)
IEEE DOI 1709
BibRef
Earlier:
Semantic Segmentation of Earth Observation Data Using Multimodal and Multi-scale Deep Networks,
ACCV16(I: 180-196).
Springer DOI 1704
Buildings, Labeling, Optical imaging, Roads, Semantics, Sensors, Training BibRef

Huang, Q.[Qin], Xia, C.Y.[Chun-Yang], Zheng, W.[Wenchao], Song, Y.H.[Yu-Hang], Xu, H.[Hao], Kuo, C.C.J.[C.C. Jay],
Object Boundary Guided Semantic Segmentation,
ACCV16(I: 197-212).
Springer DOI 1704
BibRef

Hazirbas, C.[Caner], Ma, L.[Lingni], Domokos, C.[Csaba], Cremers, D.[Daniel],
FuseNet: Incorporating Depth into Semantic Segmentation via Fusion-Based CNN Architecture,
ACCV16(I: 213-228).
Springer DOI 1704
BibRef

Bouachir, W., Torabi, A., Bilodeau, G.A., Blais, P.,
A bag of words approach for semantic segmentation of monitored scenes,
ISIVC16(88-93)
IEEE DOI 1704
Bayes methods BibRef

Souly, N.[Nasim], Shah, M.[Mubarak],
Scene Labeling Using Sparse Precision Matrix,
CVPR16(3650-3658)
IEEE DOI 1612
BibRef

Xu, C., Corso, J.J.[Jason J.],
Actor-Action Semantic Segmentation with Grouping Process Models,
CVPR16(3083-3092)
IEEE DOI 1612
BibRef

Hong, S., Oh, J., Lee, H., Han, B.,
Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network,
CVPR16(3204-3212)
IEEE DOI 1612
BibRef

Gao, Y.[Yang], Beijbom, O.[Oscar], Zhang, N.[Ning], Darrell, T.J.[Trevor J.],
Compact Bilinear Pooling,
CVPR16(317-326)
IEEE DOI 1612
BibRef

Qi, G.J.[Guo-Jun],
Hierarchically Gated Deep Networks for Semantic Segmentation,
CVPR16(2267-2275)
IEEE DOI 1612
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

Bearman, A.[Amy], Russakovsky, O.[Olga], Ferrari, V.[Vittorio], Fei-Fei, L.[Li],
What's the Point: Semantic Segmentation with Point Supervision,
ECCV16(VII: 549-565).
Springer DOI 1611
BibRef

Shimoda, W.[Wataru], Yanai, K.[Keiji],
Distinct Class-Specific Saliency Maps for Weakly Supervised Semantic Segmentation,
ECCV16(IV: 218-234).
Springer DOI 1611
BibRef

Ghiasi, G.[Golnaz], Fowlkes, C.C.[Charless C.],
Laplacian Pyramid Reconstruction and Refinement for Semantic Segmentation,
ECCV16(III: 519-534).
Springer DOI 1611
BibRef

Fourure, D.[Damien], Emonet, R.[Rémi], Fromont, E.[Elisa], Muselet, D.[Damien], Trémeau, A.[Alain], Wolf, C.[Christian],
Semantic Segmentation via Multi-task, Multi-domain Learning,
SSSPR16(333-343).
Springer DOI 1611
BibRef

Krapac, J.[Josip], Šegvic, I.K.S.[I.K. Siniša],
Ladder-Style DenseNets for Semantic Segmentation of Large Natural Images,
CVRoads17(238-245)
IEEE DOI 1802
BibRef
Earlier:
Weakly-Supervised Semantic Segmentation by Redistributing Region Scores Back to the Pixels,
GCPR16(377-388).
Springer DOI 1611
Convolution, Image segmentation, Semantics, Spatial resolution, Tensile stress, Training BibRef

Krešo, I.[Ivan], Cauševic, D.[Denis], Krapac, J.[Josip], Šegvic, I.K.S.[I.K. Siniša],
Convolutional Scale Invariance for Semantic Segmentation,
GCPR16(64-75).
Springer DOI 1611
BibRef

Xing, F.Z., Cambria, E., Huang, W.B., Xu, Y.,
Weakly supervised semantic segmentation with superpixel embedding,
ICIP16(1269-1273)
IEEE DOI 1610
Context BibRef

Tarashima, S., Pan, J., Irie, G., Kurozumi, T., Kinebuchi, T.,
Joint object discovery and segmentation with image-wise reconstruction error,
ICIP16(849-853)
IEEE DOI 1610
Airplanes BibRef

Zhou, H., Zhang, J.[Jun], Lei, J.[Jun], Li, S.[Shuohao], Tu, D.[Dan],
Image semantic segmentation based on FCN-CRF model,
ICIVC16(9-14)
IEEE DOI 1610
feature extraction BibRef

Li, W.[Weihao], Yang, M.Y.[Michael Ying],
Efficient Semantic Segmentation Of Man-made Scenes Using Fully-connected Conditional Random Field,
ISPRS16(B3: 633-640).
DOI Link 1610
BibRef

Tian, Q., Li, B.,
Simultaneous semantic segmentation of a set of partially labeled images,
WACV16(1-9)
IEEE DOI 1606
Computer science BibRef

Najafi, M.[Mohammad], Namin, S.T.[Sarah Taghavi], Salzmann, M.[Mathieu], Petersson, L.[Lars],
Sample and Filter: Nonparametric Scene Parsing via Efficient Filtering,
CVPR16(607-615)
IEEE DOI 1612
BibRef
Earlier: A2, A1, A3, A4:
Cutting Edge: Soft Correspondences in Multimodal Scene Parsing,
ICCV15(1188-1196)
IEEE DOI 1602
Feature extraction. combine modalities. BibRef

Qi, X.J.[Xiao-Juan], Liu, Z.Z.[Zheng-Zhe], Shi, J.P.[Jian-Ping], Zhao, H.S.[Heng-Shuang], Jia, J.Y.[Jia-Ya],
Augmented Feedback in Semantic Segmentation Under Image Level Supervision,
ECCV16(VIII: 90-105).
Springer DOI 1611
BibRef

Qi, X.J.[Xiao-Juan], Shi, J.P.[Jian-Ping], Liu, S., Liao, R., Jia, J.Y.[Jia-Ya],
Semantic Segmentation with Object Clique Potential,
ICCV15(2587-2595)
IEEE DOI 1602
Computational modeling BibRef

Varas, D., Alfaro, M., Marques, F.,
Multiresolution Hierarchy Co-Clustering for Semantic Segmentation in Sequences with Small Variations,
ICCV15(4579-4587)
IEEE DOI 1602
Image resolution BibRef

Deng, Z., Todorovic, S., Latecki, L.J.,
Semantic Segmentation of RGBD Images with Mutex Constraints,
ICCV15(1733-1741)
IEEE DOI 1602
Computational modeling BibRef

Pourian, N., Karthikeyan, S., Manjunath, B.S.,
Weakly Supervised Graph Based Semantic Segmentation by Learning Communities of Image-Parts,
ICCV15(1359-1367)
IEEE DOI 1602
Correlation BibRef

Caesar, H.[Holger], Uijlings, J.[Jasper], Ferrari, V.[Vittorio],
Region-Based Semantic Segmentation with End-to-End Training,
ECCV16(I: 381-397).
Springer DOI 1611
BibRef
Earlier:
Joint Calibration for Semantic Segmentation,
BMVC15(xx-yy).
DOI Link 1601
BibRef

Srivatsa, R.S.[R. Sai], Babu, R.V.[R. Venkatesh],
Salient object detection via objectness measure,
ICIP15(4481-4485)
IEEE DOI 1512
Image Saliency; Image Segmentation; Objectness Proposals; Superpixels BibRef

Ran, L.Y.[Ling-Yan], Zhang, Y.N.[Yan-Ning], Hua, G.[Gang],
CANNET: Context aware nonlocal convolutional networks for semantic image segmentation,
ICIP15(4669-4673)
IEEE DOI 1512
Semantic segmentation; context aware module; sparse kernel BibRef

Ventura, C.[Carles], Giro-i-Nieto, X.[Xavier], Vilaplana, V.[Veronica], McGuinness, K.[Kevin], Marques, F.[Ferran], O'Connor, N.E.[Noel E.],
Improving spatial codification in semantic segmentation,
ICIP15(3605-3609)
IEEE DOI 1512
Object recognition BibRef

Zhao, N.[Nan], Banerjee, C.[Chaity], Liu, X.W.[Xiu-Wen],
Nano-scale context-sensitive semantic segmentation,
ICIP15(3062-3066)
IEEE DOI 1512
Nano-scale; context-sensitive; microvilli; semantic segmentation; spike BibRef

Pieck, M.A.R.[Martin A.R.], van der Sommen, F.[Fons], Zinger, S.[Svitlana], de With, P.H.N.[Peter H.N.],
Real-time semantic context labeling for image understanding,
ICIP15(3180-3184)
IEEE DOI 1512
Context classification; Gabor filtering; SVM; Segmentation BibRef

Dai, J.F.[Ji-Feng], He, K.M.[Kai-Ming], Sun, J.[Jian],
Convolutional feature masking for joint object and stuff segmentation,
CVPR15(3992-4000)
IEEE DOI 1510
BibRef

Mostajabi, M.[Mohammadreza], Yadollahpour, P.[Payman], Shakhnarovich, G.[Gregory],
Feedforward semantic segmentation with zoom-out features,
CVPR15(3376-3385)
IEEE DOI 1510
BibRef

Zhang, W.[Wei], Zeng, S.[Sheng], Wang, D.[Dequan], Xue, X.Y.[Xiang-Yang],
Weakly supervised semantic segmentation for social images,
CVPR15(2718-2726)
IEEE DOI 1510
BibRef

Ardeshir, S.[Shervin], Collins-Sibley, K.M.[Kofi Malcolm], Shah, M.[Mubarak],
Geo-semantic segmentation,
CVPR15(2792-2799)
IEEE DOI 1510
BibRef

Sharma, A.[Abhishek], Tuzel, O.[Oncel], Jacobs, D.W.[David W.],
Deep hierarchical parsing for semantic segmentation,
CVPR15(530-538)
IEEE DOI 1510
BibRef

Samrouth, K., Deforges, O., Liu, Y.[Yi], Falou, W., Khalil, M.,
A joint 3D image semantic segmentation and scalable coding scheme with ROI approach,
VCIP14(270-273)
IEEE DOI 1504
data compression BibRef

Namin, S.T.[Sarah Taghavi], Najafi, M.[Mohammad], Salzmann, M.[Mathieu], Petersson, L.[Lars],
A Multi-modal Graphical Model for Scene Analysis,
WACV15(1006-1013)
IEEE DOI 1503
Graphical models 2D-3D data. Semantic segmentation. BibRef

Zhu, G.[Gao], Ming, Y.S.[Yan-Sheng], Li, H.D.[Hong-Dong],
Object category detection by incorporating mid-level grouping cues,
ICIP14(1604-1608)
IEEE DOI 1502
Computer vision BibRef

Bassiouny, A.[Ahmed], El-Saban, M.[Motaz],
Semantic segmentation as image representation for scene recognition,
ICIP14(981-985)
IEEE DOI 1502
Accuracy BibRef

Tegen, A.[Agnes], Weegar, R.[Rebecka], Hammarlund, L.[Linus], Oskarsson, M.[Magnus], Jiang, F.Y.[Fang-Yuan], Medved, D.[Dennis], Nugues, P.[Pierre], Astrom, K.[Kalle],
Image Segmentation and Labeling Using Free-Form Semantic Annotation,
ICPR14(2281-2286)
IEEE DOI 1412
Context BibRef

Kroeger, T.[Thorben], Kappes, J.H.[Jörg H.], Beier, T.[Thorsten], Koethe, U.[Ullrich], Hamprecht, F.A.[Fred A.],
Asymmetric Cuts: Joint Image Labeling and Partitioning,
GCPR14(199-211).
Springer DOI 1411
BibRef

Mustikovela, S.K.[Siva Karthik], Yang, M.Y.[Michael Ying], Rother, C.[Carsten],
Can Ground Truth Label Propagation from Video Help Semantic Segmentation?,
VSeg16(III: 804-820).
Springer DOI 1611
BibRef

Zheng, S.[Shuai], Cheng, M.M.[Ming-Ming], Warrell, J.[Jonathan], Sturgess, P.[Paul], Vineet, V.[Vibhav], Rother, C.[Carsten], Torr, P.H.S.[Philip H.S.],
Dense Semantic Image Segmentation with Objects and Attributes,
CVPR14(3214-3221)
IEEE DOI 1409
Attributes; Image Segmentation; Object Recognition; Scene Understanding BibRef

Ladicky, L.[Lubor], Shi, J.B.[Jian-Bo], Pollefeys, M.[Marc],
Pulling Things out of Perspective,
CVPR14(89-96)
IEEE DOI 1409
Depth Estimation; Object Recognition; Semantic Segmentation 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

Mottaghi, R.[Roozbeh], Chen, X.J.[Xian-Jie], Liu, X.B.[Xiao-Bai], Cho, N.G.[Nam-Gyu], Lee, S.W.[Seong-Whan], Fidler, S.[Sanja], Urtasun, R.[Raquel], Yuille, A.L.[Alan L.],
The Role of Context for Object Detection and Semantic Segmentation in the Wild,
CVPR14(891-898)
IEEE DOI 1409
BibRef

Isola, P.[Phillip], Zoran, D.[Daniel], Krishnan, D.[Dilip], Adelson, E.H.[Edward H.],
Crisp Boundary Detection Using Pointwise Mutual Information,
ECCV14(III: 799-814).
Springer DOI 1408
Between semantic objects. BibRef

Li, Z.Y.[Zhen-Yang], Gavves, E.[Efstratios], Mensink, T.[Thomas], Snoek, C.G.M.[Cees G.M.],
Attributes Make Sense on Segmented Objects,
ECCV14(VI: 350-365).
Springer DOI 1408
BibRef

Dong, J.[Jian], Chen, Q.A.[Qi-Ang], Yan, S.C.[Shui-Cheng], Yuille, A.L.[Alan L.],
Towards Unified Object Detection and Semantic Segmentation,
ECCV14(V: 299-314).
Springer DOI 1408
Joint detect and segment. BibRef

Kundu, A.[Abhijit], Li, Y.[Yin], Dellaert, F.[Frank], Li, F.X.[Fu-Xin], Rehg, J.M.[James M.],
Joint Semantic Segmentation and 3D Reconstruction from Monocular Video,
ECCV14(VI: 703-718).
Springer DOI 1408
BibRef

Inagaki, S.[Shun], Imiya, A.[Atsushi],
Semantic Segmentation of Low Frame-Rate Image Sequence Using Statistical Properties of Optical Flow for Remote Exploration,
ISVC14(I: 477-488).
Springer DOI 1501
BibRef
And:
Statistical Method for Semantic Segmentation of Dominant Plane from Remote Exploration Image Sequence,
SSSPR14(263-272).
Springer DOI 1408
BibRef

Riemenschneider, H.[Hayko], Bódis-Szomorú, A.[András], Weissenberg, J.[Julien], Van Gool, L.J.[Luc J.],
Learning Where to Classify in Multi-view Semantic Segmentation,
ECCV14(V: 516-532).
Springer DOI 1408
BibRef

Tao, L.L.[Ling-Ling], Porikli, F.M.[Fatih M.], Vidal, R.[René],
Sparse Dictionaries for Semantic Segmentation,
ECCV14(V: 549-564).
Springer DOI 1408
BibRef

Zhu, S.Q.[Sheng-Qi], Yang, Y.Q.[Yi-Qing], Zhang, L.[Li],
From Label Maps to Label Strokes: Semantic Segmentation for Street Scenes from Incomplete Training Data,
CVCP13(468-475)
IEEE DOI 1403
data handling BibRef

Baek, S.[Seung_Ryul], Lim, T.[Taegyu], Heo, Y.S.[Yong Seok], Park, S.B.[Sung-Bum], Kwak, H.[Hantak], Shim, W.[Woosung],
Superpixel Coherency and Uncertainty Models for Semantic Segmentation,
PGMs13(275-282)
IEEE DOI 1403
computational complexity BibRef

Roig, G.[Gemma], Boix, X.[Xavier], de Nijs, R.[Roderick], Ramos, S.[Sebastian], Kuhnlenz, K.[Koljia], Van Gool, L.J.[Luc J.],
Active MAP Inference in CRFs for Efficient Semantic Segmentation,
ICCV13(2312-2319)
IEEE DOI 1403
using expensive features. BibRef

Barron, J.T.[Jonathan T.], Biggin, M.D.[Mark D.], Arbelaez, P.[Pablo], Knowles, D.W.[David W.], Keranen, S.V.E.[Soile V.E.], Malik, J.[Jitendra],
Volumetric Semantic Segmentation Using Pyramid Context Features,
ICCV13(3448-3455)
IEEE DOI 1403
BibRef

Singh, G.[Gautam], Kosecka, J.[Jana],
Introspective semantic segmentation,
WACV14(714-720)
IEEE DOI 1406
BibRef
Earlier:
Nonparametric Scene Parsing with Adaptive Feature Relevance and Semantic Context,
CVPR13(3151-3157)
IEEE DOI 1309
feature relevance; scene understanding; semantic segmentation. Small patches, simple features. Accuracy. BibRef

Csurka, G.[Gabriela], Larlus, D.[Diane], Perronnin, F.[Florent],
What is a good evaluation measure for semantic segmentation?,
BMVC13(xx-yy).
DOI Link 1402
BibRef

Li, F.X.[Fu-Xin], Carreira, J.[Joao], Lebanon, G.[Guy], Sminchisescu, C.[Cristian],
Composite Statistical Inference for Semantic Segmentation,
CVPR13(3302-3309)
IEEE DOI 1309
composite likelihood BibRef

Ying, P.[Peng], Liu, J.[Jing], Lu, H.Q.[Han-Qing],
Dictionary learning based superpixels clustering for weakly-supervised semantic segmentation,
ICIP15(4258-4262)
IEEE DOI 1512
Weak supervision;dictionary learning;semantic segmentation BibRef

Liu, Y.[Yang], Liu, J.[Jing], Li, Z.[Zechao], Tang, J.H.[Jin-Hui], Lu, H.Q.[Han-Qing],
Weakly-Supervised Dual Clustering for Image Semantic Segmentation,
CVPR13(2075-2082)
IEEE DOI 1309
Image Semantic Segmentation; Weakly-Supervised BibRef

Zou, W.B.[Wen-Bin], Kpalma, K.[Kidiyo], Ronsin, J.[Joseph],
Semantic image segmentation using region bank,
ICPR12(922-925).
WWW Link. 1302
BibRef
And:
Semantic segmentation via sparse coding over hierarchical regions,
ICIP12(2577-2580).
IEEE DOI 1302
Hierarchical region segmentation, sparse coding of regions for recognition. BibRef

Fröhlich, B.[Björn], Rodner, E.[Erik], Denzler, J.[Joachim],
Semantic Segmentation with Millions of Features: Integrating Multiple Cues in a Combined Random Forest Approach,
ACCV12(I:218-231).
Springer DOI 1304
BibRef
And:
As Time Goes by: Anytime Semantic Segmentation with Iterative Context Forests,
DAGM12(1-10).
Springer DOI 1209
BibRef

Hariharan, B.[Bharath], Zitnick, C.L.[C. Lawrence], Dollar, P.[Piotr],
Detecting Objects Using Deformation Dictionaries,
CVPR14(1995-2002)
IEEE DOI 1409
BibRef

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

Lin, D.[Dahua], Fidler, S.[Sanja], Urtasun, R.[Raquel],
Holistic Scene Understanding for 3D Object Detection with RGBD Cameras,
ICCV13(1417-1424)
IEEE DOI 1403
BibRef

Fidler, S.[Sanja], Mottaghi, R.[Roozbeh], Yuille, A.L.[Alan L.], Urtasun, R.[Raquel],
Bottom-Up Segmentation for Top-Down Detection,
CVPR13(3294-3301)
IEEE DOI 1309
Object detection; object class recognition; object segmentation BibRef

Yao, J.[Jian], Fidler, S.[Sanja], Urtasun, R.[Raquel],
Describing the scene as a whole: Joint object detection, scene classification and semantic segmentation,
CVPR12(702-709).
IEEE DOI 1208
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

Dunlop, H.[Heather],
Scene classification of images and video via semantic segmentation,
POCV10(72-79).
IEEE DOI 1006
BibRef

Pohlen, T., Badami, I., Mathias, M., Leibe, B.[Bastian],
Semantic segmentation of modular furniture,
WACV16(1-9)
IEEE DOI 1606
Face BibRef

Floros, G.[Georgios], Leibe, B.[Bastian],
Joint 2D-3D temporally consistent semantic segmentation of street scenes,
CVPR12(2823-2830).
IEEE DOI 1208
BibRef

Floros, G.[Georgios], Rematas, K.[Konstantinos], Leibe, B.[Bastian],
Multi-Class Image Labeling with Top-Down Segmentation and Generalized Robust P^N Potentials,
BMVC11(xx-yy).
HTML Version. 1110
BibRef

Passino, G.[Giuseppe], Patras, I.[Ioannis], Izquierdo, E.[Ebroul],
Pyramidal Model for Image Semantic Segmentation,
ICPR10(1554-1557).
IEEE DOI 1008
BibRef

Micusik, B.[Branislav], Kosecka, J.[Jana],
Semantic segmentation of street scenes by superpixel co-occurrence and 3D geometry,
ObjectEvent09(625-632).
IEEE DOI 0910
identify as one of a few common object/background classes. BibRef

Schnitman, Y.[Yaar], Caspi, Y.[Yaron], Cohen-Or, D.[Daniel], Lischinski, D.[Dani],
Inducing Semantic Segmentation from an Example,
ACCV06(II:373-384).
Springer DOI 0601
BibRef

Zhang, H.H.[Hong-Hui], Xiao, J.X.[Jian-Xiong], Quan, L.[Long],
Supervised Label Transfer for Semantic Segmentation of Street Scenes,
ECCV10(V: 561-574).
Springer DOI 1009
Set of labelled images of street scenes. Recognition is by matching at image level, then using the given lables. BibRef

Chapter on 2-D Region Segmentation Techniques, Snakes, Active Contours continues in
Fua and Leclerc Guided Segmentation Papers .

Last update:Nov 12, 2018 at 11:26:54