Integrating parametric and non-parametric models for scene labeling

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn 07-12-June-2015, Issue , 2015, Pages 4249-4258

  Shuai, Bing ^a   Wang, Gang ^a   Zuo, Zhen ^a   Wang, Bing ^a   Zhao, Lifan ^a  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

[No Author keywords available]

Indexed keywords

BENCHMARKING; COMPUTER VISION; NEURAL NETWORKS; PIXELS;

CLASS PREDICTION; CONVOLUTIONAL NEURAL NETWORK; DISCRIMINATIVE FEATURES; NON-PARAMETRIC MODEL; PARAMETRIC MODELING; POTENTIAL ESTIMATION; SCENE CONSTRAINTS; STATE-OF-THE-ART PERFORMANCE;

PATTERN RECOGNITION;

EID: 84937133497     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2015.7299053     Document Type: Conference Paper

References (39)

1. S. R. Bulo and P. Kontschieder. Neural decision forests for semantic image labelling. In Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on. IEEE, 2014
2. J. Donahue, Y. Jia, O. Vinyals, J. Hoffman, N. Zhang, E. Tzeng, and T. Darrell. Decaf: A deep convolutional activation feature for generic visual recognition. In Proceedings of The 31st International Conference on Machine Learning, pages 647-655, 2014
3. D. Eigen and R. Fergus. Nonparametric image parsing using adaptive neighbor sets. In Computer vision and pattern recognition (CVPR), 2012 IEEE Conference on, pages 2799-2806. IEEE, 2012
4. C. Farabet, C. Couprie, L. Najman, and Y. LeCun. Learning hierarchical features for scene labeling. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 35(8):1915-1929, 2013
5. C. Gatta, A. Romero, and J. van de Veijer. Unrolling loopy top-down semantic feedback in convolutional deep networks. In Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on. IEEE, 2014
6. S. Gould, R. Fulton, and D. Koller. Decomposing a scene into geometric and semantically consistent regions. In Computer Vision, 2009 IEEE 12th International Conference on, pages 1-8. IEEE, 2009
7. S. Gould and Y. Zhang. Patchmatchgraph: Building a graph of dense patch correspondences for label transfer. In Computer Vision-ECCV 2012, pages 439-452. Springer, 2012
8. S. Gould, J. Zhao, X. He, and Y. Zhang. Superpixel graph label transfer with learned distance metric. In Computer Vision-ECCV 2014, pages 632-647. Springer, 2014
9. X. He, R. S. Zemel, and M. Carreira-Perpinan. Multiscale conditional random fields for image labeling. In Computer vision and pattern recognition, 2004. CVPR 2004. Proceedings of the 2004 IEEE computer society conference on, volume 2, pages II-695. IEEE, 2004
10. J. Hu, J. Lu, and Y.-P. Tan. Discriminative deep metric learning for face verification in the wild. In Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on, pages 1875-1882. IEEE, 2014
11. P. Kohli, P. H. Torr, et al. Robust higher order potentials for enforcing label consistency. International Journal of Computer Vision, 82(3):302-324, 2009
12. P. Kontschieder, S. R. Bulo, H. Bischof, and M. Pelillo. Structured class-labels in random forests for semantic image labelling. In Computer Vision (ICCV), 2011 IEEE International Conference on, pages 2190-2197. IEEE, 2011
13. A. Krizhevsky, I. Sutskever, and G. E. Hinton. Imagenet classification with deep convolutional neural networks. In Advances in neural information processing systems, pages 1097-1105, 2012
14. S. Lazebnik, C. Schmid, and J. Ponce. Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories. In Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on, volume 2, pages 2169-2178. IEEE, 2006
15. Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner. Gradientbased learning applied to document recognition. Proceedings of the IEEE, 86(11):2278-2324, 1998
16. C. Liu, J. Yuen, and A. Torralba. Nonparametric scene parsing: Label transfer via dense scene alignment. In Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on, pages 1972-1979. IEEE, 2009
17. D. G. Lowe. Distinctive image features from scaleinvariant keypoints. International journal of computer vision, 60(2):91-110, 2004
18. P. Márquez-Neila, P. Kohli, C. Rother, and L. Baumela. Nonparametric higher-order random fields for image segmentation. In Computer Vision-ECCV 2014, pages 269-284. Springer, 2014
19. A. Oliva and A. Torralba. Building the gist of a scene: The role of global image features in recognition. Progress in brain research, 155:23-36, 2006
20. M. Oquab, L. Bottou, I. Laptev, J. Sivic, et al. Learning and transferring mid-level image representations using convolutional neural networks. In Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on. IEEE, 2014
21. P. Pinheiro and R. Collobert. Recurrent convolutional neural networks for scene labeling. In Proceedings of The 31st International Conference on Machine Learning, pages 82-90, 2014
22. A. Roy and S. Todorovic. Scene labeling using beam search under mutex constraints. In Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on. IEEE, 2014
23. J. Shotton, J. Winn, C. Rother, and A. Criminisi. Textonboost: Joint appearance, shape and context modeling for multi-class object recognition and segmentation. In Computer Vision-ECCV 2006, pages 1-15. Springer, 2006
24. G. Singh and J. Kosecka. Nonparametric scene parsing with adaptive feature relevance and semantic context. In Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on, pages 3151-3157. IEEE, 2013
25. J. Tighe and S. Lazebnik. Superparsing: scalable nonparametric image parsing with superpixels. In Computer Vision-ECCV 2010, pages 352-365. Springer, 2010
26. J. Tighe and S. Lazebnik. Finding things: Image parsing with regions and per-exemplar detectors. In Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on, pages 3001-3008. IEEE, 2013
27. J. Tompson, A. Jain, Y. LeCun, and C. Bregler. Joint training of a convolutional network and a graphical model for human pose estimation. In NIPS, 2014
28. A. Toshev and C. Szegedy. Deeppose: Human pose estimation via deep neural networks. arXiv preprint arXiv:1312. 4659, 2013
29. F. Tung and J. J. Little. Collageparsing: Nonparametric scene parsing by adaptive overlapping windows. In Computer Vision-ECCV 2014, pages 511-525. Springer, 2014
30. A. Vedaldi and K. Lenc. Matconvnet-convolutional neural networks for matlab. CoRR, abs/1412. 4564, 2014
31. A. Wang, J. Lu, G. Wang, J. Cai, and T.-J. Cham. Multimodal unsupervised feature learning for rgb-d scene labeling. In Computer Vision-ECCV 2014, pages 453-467. Springer, 2014
32. L. Wang, T. Liu, G. Wang, K. L. Chan, and Q. Yang. Video tracking using learned hierarchical features. Image Processing, IEEE Transactions on, 24(4):1424-1435, 2015
33. L. Wolf. Deepface: Closing the gap to human-level performance in face verification. In Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on. IEEE, 2014
34. J. Yang, B. Price, S. Cohen, and M.-H. Yang. Context driven scene parsing with attention to rare classes. In Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on. IEEE, 2014
35. M. D. Zeiler and R. Fergus. Visualizing and understanding convolutional networks. In Computer Vision-ECCV 2014, pages 818-833. Springer, 2014
36. N. Zhang, M. Paluri, M. Ranzato, T. Darrell, and L. Bourdev. Panda: Pose aligned networks for deep attribute modeling. arXiv preprint arXiv:1311. 5591, 2013
37. Y. Zhang and T. Chen. Efficient inference for fullyconnected crfs with stationarity. In Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on, pages 582-589. IEEE, 2012
38. Z. Zuo, G. Wang, B. Shuai, L. Zhao, and Q. Yang. Exemplar based deep discriminative and shareable feature learning for scene image classification. Pattern Recognition, 2015
39. Z. Zuo, G. Wang, B. Shuai, L. Zhao, Q. Yang, and X. Jiang. Learning discriminative and shareable features for scene classification. In Computer Vision-ECCV 2014, pages 552-568. Springer, 2014.