Bottom-up instance segmentation using deep higher-order CRFs

British Machine Vision Conference 2016, BMVC 2016

Volumn 2016-September, Issue , 2016, Pages 9.1-9.12

  Arnab, Anurag ^a   Torr, Philip H S ^a  

^a UNIVERSITY OF OXFORD   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; DEEP NEURAL NETWORKS; IMAGE SEGMENTATION; OBJECT RECOGNITION; PIXELS; SEMANTICS;

CONDITIONAL RANDOM FIELD; HIGHER ORDER POTENTIALS; HIGHER-ORDER; OBJECT DETECTORS; PIXEL LEVEL; SCENE UNDERSTANDING; SEMANTIC SEGMENTATION; SIMPLE METHOD;

OBJECT DETECTION;

EID: 85044534252     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.5244/C.30.19     Document Type: Conference Paper

References (38)

1. Pablo Arbelaez, Jordi Pont-Tuset, Jon Barron, Ferran Marques, and Jitendra Malik. Multiscale combinatorial grouping. In CVPR, pages 328–335. IEEE, 2014.
2. Anurag Arnab, Sadeep Jayasumana, Shuai Zheng, and Philip H. S. Torr. Higher order potentials in end-to-end trainable conditional random fields. In ECCV, 2016.
3. Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, and Alan L Yuille. Semantic image segmentation with deep convolutional nets and fully connected crfs. ICLR, 2015.
4. Yi-Ting Chen, Xiaokai Liu, and Ming-Hsuan Yang. Multi-instance object segmentation with occlusion handling. In CVPR, pages 3470–3478, 2015.
5. Jifeng Dai, Kaiming He, and Jian Sun. Convolutional feature masking for joint object and stuff segmentation. In CVPR, 2015.
6. Jifeng Dai, Kaiming He, and Jian Sun. Boxsup: Exploiting bounding boxes to supervise convolutional networks for semantic segmentation. In ICCV, 2015.
7. Jifeng Dai, Kaiming He, and Jian Sun. Instance-aware semantic segmentation via multi-task network cascades. In CVPR, 2016.
8. Mark Everingham, Luc Van Gool, Christopher KI Williams, John Winn, and Andrew Zisserman. The pascal visual object classes (voc) challenge. IJCV, 2010.
9. Pedro Felzenszwalb, David McAllester, and Deva Ramanan. A discriminatively trained, multiscale, deformable part model. In CVPR, pages 1–8. IEEE, 2008.
10. Spyros Gidaris and Nikos Komodakis. Object detection via a multi-region and semantic segmentation-aware cnn model. In ICCV, pages 1134–1142, 2015.
11. Ross Girshick. Fast r-cnn. In ICCV, 2015.
12. Ross Girshick, Jeff Donahue, Trevor Darrell, and Jitendra Malik. Rich feature hierarchies for accurate object detection and semantic segmentation. In CVPR, 2014.
13. Bharath Hariharan, Pablo Arbel ez, Ross Girshick, and Jitendra Malik. Simultaneous detection and segmentation. In ECCV, pages 297–312. Springer, 2014.
14. Bharath Hariharan, Pablo Arbel ez, Ross Girshick, and Jitendra Malik. Hypercolumns for object segmentation and fine-grained localization. CVPR, 2015.
15. Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. Spatial pyramid pooling in deep convolutional networks for visual recognition. In ECCV, 2014.
16. Xuming He, Richard S Zemel, and Miguel Carreira-Perpi n. Multiscale conditional random fields for image labeling. In CVPR, volume 2, pages II–695. IEEE, 2004.
17. Pushmeet Kohli, Lubor Ladicky, and Philip H.S. Torr. Robust higher order potentials for enforcing label consistency. IJCV, 82(3):302–324, 2009.
18. P. Kr henb hl and V. Koltun. Efficient inference in fully connected CRFs with Gaussian edge potentials. In NIPS, 2011.
19. Alex Krizhevsky, Ilya Sutskever, and Geoffrey E. Hinton. Imagenet classification with deep convolutional neural networks. In NIPS, pages 1097–1105. 2012.
20. Lubor Ladicky, Chris Russell, Pushmeet Kohli, and Philip HS Torr. Graph cut based inference with co-occurrence statistics. In ECCV, pages 239–253. 2010.
21. Lubor Ladick, Paul Sturgess, Karteek Alahari, Chris Russell, and Philip H. S. Torr. What, where and how many? combining object detectors and crfs. In ECCV, pages 424–437, 2010.
22. Yann LeCun, L on Bottou, Yoshua Bengio, and Patrick Haffner. Gradient-based learning applied to document recognition. Proceedings of the IEEE, 86(11):2278–2324, 1998.
23. Xiaodan Liang, Yunchao Wei, Xiaohui Shen, Zequn Jie, Jiashi Feng, Liang Lin, and Shuicheng Yan. Reversible recursive instance-level object segmentation. arXiv preprint arXiv:1511.04517, 2015.
24. Xiaodan Liang, Yunchao Wei, Xiaohui Shen, Jianchao Yang, Liang Lin, and Shuicheng Yan. Proposal-free network for instance-level object segmentation. arXiv preprint arXiv:1509.02636, 2015.
25. Guosheng Lin, Chunhua Shen, Ian Reid, et al. Efficient piecewise training of deep structured models for semantic segmentation. In CVPR, 2016.
26. Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Doll r, and C Lawrence Zitnick. Microsoft coco: Common objects in context. In ECCV, pages 740–755. Springer, 2014.
27. Jonathan Long, Evan Shelhamer, and Trevor Darrell. Fully convolutional networks for semantic segmentation. In CVPR, 2015.
28. Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun. Faster R-CNN: Towards real-time object detection with region proposal networks. In NIPS, 2015.
29. Bernardino Romera-Paredes and Philip HS Torr. Recurrent instance segmentation. In ECCV, 2016.
30. Carsten Rother, Vladimir Kolmogorov, and Andrew Blake. Grabcut: Interactive foreground extraction using iterated graph cuts. ACM TOG, 2004.
31. Jamie Shotton, John Winn, Carsten Rother, and Antonio Criminisi. Textonboost for image understanding: Multi-class object recognition and segmentation by jointly modeling texture, layout, and context. IJCV, 2009.
32. Karen Simonyan and Andrew Zisserman. Very deep convolutional networks for large-scale image recognition. In ICLR, 2015.
33. Min Sun, Byung-soo Kim, Pushmeet Kohli, and Silvio Savarese. Relating things and stuff via object property interactions. PAMI, 36(7):1370–1383, 2014.
34. Jasper RR Uijlings, Koen EA van de Sande, Theo Gevers, and Arnold WM Smeulders. Selective search for object recognition. IJCV, 104(2):154–171, 2013.
35. Vibhav Vineet, Jonathan Warrell, and Philip HS Torr. Filter-based mean-field inference for random fields with higher-order terms and product label-spaces. IJCV, 2014.
36. Jian Yao, Sanja Fidler, and Raquel Urtasun. Describing the Scene as a Whole: Joint Object Detection, Scene Classification and Semantic Segmentation. In CVPR, pages 702–709, 2012.
37. Fisher Yu and Vladlen Koltun. Multi-scale context aggregation by dilated convolutions. In ICLR, 2016.
38. Shuai Zheng, Sadeep Jayasumana, Bernardino Romera-Paredes, Vibhav Vineet, Zhizhong Su, Dalong Du, Chang Huang, and Philip Torr. Conditional random fields as recurrent neural networks. In ICCV, 2015.