Scene parsing through ADE20K dataset

Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017

Volumn 2017-January, Issue , 2017, Pages 5122-5130

  Zhou, Bolei ^a   Zhao, Hang ^a   Puig, Xavier ^a   Fidler, Sanja ^b   Barriuso, Adela ^a   Torralba, Antonio ^a  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^b UNIVERSITY OF TORONTO   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; IMAGE ANNOTATION; IMAGE PROCESSING; PATTERN RECOGNITION;

BASELINE MODELS; DATA COLLECTION; IMAGE CONTENT; IMAGE DATASETS; NETWORK DESIGN; OBJECT CATEGORIES;

FORMAL LANGUAGES;

EID: 85041896881     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2017.544     Document Type: Conference Paper

References (35)

1. V. Badrinarayanan, A. Kendall, and R. Cipolla. Segnet: A deep convolutional encoder-decoder architecture for image segmentation. arXiv:1511.00561, 2015.
2. S. Bell, P. Upchurch, N. Snavely, and K. Bala. OpenSurfaces: A richly annotated catalog of surface appearance. ACM Trans. on Graphics (SIGGRAPH), 32(4), 2013.
3. S. Bell, P. Upchurch, N. Snavely, and K. Bala. Material recognition in the wild with the materials in context database. In Proc. CVPR, 2015.
4. L.-C. Chen, G. Papandreou, I. Kokkinos, K. Murphy, and A. L. Yuille. Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected CRFs. arXiv:1606.00915, 2016.
5. X. Chen, R. Mottaghi, X. Liu, N.-G. Cho, S. Fidler, R. Urtasun, and A. Yuille. Detect what you can: Detecting and representing objects using holistic models and body parts. In Proc. CVPR, 2014.
6. U. o. I. a. U.-C.computer Vision Group. Cross-category object recognition. In http://vision.cs.uiuc.edu/CORE/, 2009.
7. M. Cordts, M. Omran, S. Ramos, T. Scharwächter, M. Enzweiler, R. Benenson, U. Franke, S. Roth, and B. Schiele. The cityscapes dataset. In CVPR Workshop on The Future of Datasets in Vision, 2015.
8. J. Dai, K. He, and J. Sun. Convolutional feature masking for joint object and stuff segmentation. In Proc. CVPR, 2015.
9. J. Dai, K. He, and J. Sun. Instance-aware semantic segmentation via multi-task network cascades. Proc. CVPR, 2016.
10. M. Everingham, L. Van Gool, C. K. Williams, J. Winn, and A. Zisserman. The pascal visual object classes (voc) challenge. Int'l Journal of Computer Vision, 2010.
11. C. Farabet, C. Couprie, L. Najman, and Y. LeCun. Learning hierarchical features for scene labeling. IEEE Trans. on Pattern Analysis and Machine Intelligence, 2013.
12. A. Geiger, P. Lenz, and R. Urtasun. Are we ready for autonomous driving? the kitti vision benchmark suite. In Proc. CVPR, 2012.
13. G. Heitz and D. Koller. Learning spatial context: Using stuff to find things. In Proc. ECCV, 2008.
14. J.-B. Huang, S. B. Kang, N. Ahuja, and J. Kopf. Image completion using planar structure guidance. ACM Transactions on Graphics (TOG), 2014.
15. Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long, R. Girshick, S. Guadarrama, and T. Darrell. Caffe: Convolutional architecture for fast feature embedding. In Proceedings of the ACM International Conference on Multimedia. ACM, 2014.
16. A. Krizhevsky, I. Sutskever, and G. E. Hinton. Imagenet classification with deep convolutional neural networks. In Advances in neural information processing systems, 2012.
17. T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. L. Zitnick. Microsoft coco: Common objects in context. In Proc. ECCV. 2014.
18. C. Liu, J. Yuen, and A. Torralba. Nonparametric scene parsing: Label transfer via dense scene alignment. In Proc. CVPR, 2009.
19. J. Long, E. Shelhamer, and T. Darrell. Fully convolutional networks for semantic segmentation. In Proc. CVPR, 2015.
20. D. Martin, C. Fowlkes, D. Tal, and J. Malik. A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics. In Proc. ICCV, 2001.
21. R. Mottaghi, X. Chen, X. Liu, N.-G. Cho, S.-W. Lee, S. Fidler, R. Urtasun, and A. Yuille. The role of context for object detection and semantic segmentation in the wild. In Proc. CVPR, 2014.
22. P. K. Nathan Silberman, Derek Hoiem and R. Fergus. Indoor segmentation and support inference from rgbd images. In Proc. ECCV, 2012.
23. A. Nguyen, A. Dosovitskiy, J. Yosinski, T. Brox, and J. Clune. Synthesizing the preferred inputs for neurons in neural networks via deep generator networks. NIPS 2016, 2016.
24. H. Noh, S. Hong, and B. Han. Learning deconvolution network for semantic segmentation. In Proc. ICCV, 2015.
25. P. H. Pinheiro and R. Collobert. Recurrent convolutional neural networks for scene labeling. In ICML, pages 82-90, 2014.
26. O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, A. C. Berg, and L. Fei-Fei. ImageNet Large Scale Visual Recognition Challenge. Int'l Journal of Computer Vision, 115(3):211-252, 2015.
27. B. C. Russell, A. Torralba, K. P. Murphy, andW. T. Freeman. Labelme: a database and web-based tool for image annotation. Int'l Journal of Computer Vision, 2008.
28. S. Song, S. P. Lichtenberg, and J. Xiao. Sun rgb-d: A rgb-d scene understanding benchmark suite. In Proc. CVPR, 2015.
29. M. Spain and P. Perona. Measuring and predicting object importance. International Journal of Computer Vision, 2010.
30. J. Tighe and S. Lazebnik. Understanding scenes on many levels. In Proc. ICCV, 2011.
31. J. Tighe and S. Lazebnik. Finding things: Image parsing with regions and per-exemplar detectors. In Proc. CVPR, 2013.
32. J. Xiao, J. Hays, K. A. Ehinger, A. Oliva, and A. Torralba. Sun database: Large-scale scene recognition from abbey to zoo. In Proc. CVPR, 2010.
33. J. Yang, B. Price, S. Cohen, and M.-H. Yang. Context driven scene parsing with attention to rare classes. In Proc. CVPR, 2014.
34. F. Yu and V. Koltun. Multi-scale context aggregation by dilated convolutions. In ICLR, 2016.
35. B. Zhou, A. Lapedriza, J. Xiao, A. Torralba, and A. Oliva. Learning deep features for scene recognition using places database. In In Advances in Neural Information Processing Systems, 2014.