DHSNet: Deep hierarchical saliency network for salient object detection

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

Volumn 2016-December, Issue , 2016, Pages 678-686

  Liu, Nian ^a   Han, Junwei ^a  

^a NORTHWESTERN POLYTECHNICAL UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

BENCHMARKING; COMPUTER VISION; CONVOLUTION; NEURAL NETWORKS; OBJECT DETECTION; OBJECT RECOGNITION; PROGRAM PROCESSORS;

BENCHMARK DATASETS; CONVOLUTIONAL NEURAL NETWORK; GLOBAL CONTRASTS; GLOBAL PREDICTIONS; OPTIMAL COMBINATION; SALIENT OBJECT DETECTION; SALIENT OBJECTS; STATE-OF-THE-ART ALGORITHMS;

PATTERN RECOGNITION;

EID: 84986250467     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2016.80     Document Type: Conference Paper

References (42)

1. D. Simakov, Y. Caspi, E. Shechtman, and M. Irani. Summarizing visual data using bidirectional similarity. in CVPR, 2008.
2. M. Donoser, M. Urschler, M. Hirzer, and H. Bischof. Saliency driven total variation segmentation. in ICCV, 2009.
3. Y. Gao, M. Wang, Z.-J. Zha, J. Shen, X. Li, and X. Wu. Visual-textual joint relevance learning for tag-based social image search. TIP, 22 (1): 363-376, 2013.
4. C. Rother, L. Bordeaux, Y. Hamadi, and A. Blake. Autocollage. ACM Trans. Graphics (TOG), 25 (3): 847-852, 2006.
5. L. Itti, C. Koch, and E. Niebur. A model of saliency-based visual attention for rapid scene analysis. PAMI, 20 (11): 1254-1259, 1998.
6. D. A. Klein and S. Frintrop. Center-surround divergence of feature statistics for salient object detection. in ICCV, 2011.
7. M.-M. Cheng, G.-X. Zhang, N. J. Mitra, X. Huang, and S.-M. Hu. Global contrast based salient region detection. in CVPR, 2011.
8. R. Achanta, S. Hemami, F. Estrada, and S. Susstrunk. Frequency-tuned salient region detection. in CVPR, 2009.
9. J. Han, D. Zhang, X. Hu, L. Guo, J. Ren, and F. Wu. Background Prior-Based Salient Object Detection via Deep Reconstruction Residual. IEEE Trans. CSVT, 25 (8): 1309-1321, 2015.
10. C. Yang, L. Zhang, H. Lu, X. Ruan, and M.-H. Yang. Saliency detection via graph-based manifold ranking. in CVPR, 2013.
11. Y. Wei, F. Wen, W. Zhu, and J. Sun. Geodesic saliency using background priors. in ECCV, 2012.
12. F. Perazzi, P. Krahenbuhl, Y. Pritch, and A. Hornung. Saliency filters: Contrast based filtering for salient region detection. in CVPR, 2012.
13. K.-Y. Chang, T.-L. Liu, H.-T. Chen, and S.-H. Lai. Fusing generic objectness and visual saliency for salient object detection. in ICCV, 2011.
14. Y. Li, X. Hou, C. Koch, J. M. Rehg, and A. L. Yuille. The secrets of salient object segmentation. in CVPR, 2014.
15. T. Liu, Z. Yuan, J. Sun, J. Wang, N. Zheng, X. Tang, and H.-Y. Shum. Learning to detect a salient object. PAMI, 33 (2): 353-367, 2011.
16. C. Gong, D. Tao, W. Liu, S. J. Maybank, M. Fang, K. Fu, and J. Yang. Saliency Propagation from Simple to Difficult. in CVPR, 2015.
17. J. Kim, D. Han, Y.-W. Tai, and J. Kim. Salient region detection via high-dimensional color transform. in CVPR, 2014.
18. Q. Yan, L. Xu, J. Shi, and J. Jia. Hierarchical saliency detection. in CVPR, 2013.
19. H. Jiang, J. Wang, Z. Yuan, Y. Wu, N. Zheng, and S. Li. Salient object detection: A discriminative regional feature integration approach. in CVPR, 2013.
20. Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner. Gradient-based learning applied to document recognition. Proceedings of the IEEE, 86 (11): 2278-2324, 1998.
21. M. Liang and X. Hu. Recurrent Convolutional Neural Network for Object Recognition. in CVPR, 2015.
22. C. Farabet, C. Couprie, L. Najman, and Y. LeCun. Learning hierarchical features for scene labeling. PAMI, 35 (8): 1915-1929, 2013.
23. J. Long, E. Shelhamer, and T. Darrell. Fully Convolutional Networks for Semantic Segmentation. in CVPR, 2015.
24. D. Eigen, C. Puhrsch, and R. Fergus. Depth map prediction from a single image using a multi-scale deep network. in NIPS, 2014.
25. K. Simonyan and A. Zisserman. Very deep convolutional networks for large-scale image recognition. in ICLR, 2015.
26. A. Krizhevsky, I. Sutskever, and G. E. Hinton. Imagenet classification with deep convolutional neural networks. in NIPS, 2012.
27. K. He, X. Zhang, S. Ren, and J. Sun. Spatial pyramid pooling in deep convolutional networks for visual recognition. in ECCV, 2014.
28. R. Girshick, J. Donahue, T. Darrell, and J. Malik. Rich feature hierarchies for accurate object detection and semantic segmentation. in CVPR, 2014.
29. Y. Taigman, M. Yang, M. A. Ranzato, and L. Wolf. Deepface: Closing the gap to human-level performance in face verification. in CVPR, 2014.
30. H. Noh, S. Hong, and B. Han. Learning deconvolution network for semantic segmentation. in ICCV, 2015.
31. P. Fischer, A. Dosovitskiy, E. Ilg, P. Häusser, C. Hazrba, V. Golkov, P. van der Smagt, D. Cremers, and T. Brox. FlowNet: Learning Optical Flow with Convolutional Networks. in ICCV, 2015.
32. N. Liu, J. Han, D. Zhang, S. Wen, and T. Liu. Predicting eye fixations using convolutional neural networks. in CVPR, 2015.
33. M. Kümmerer, L. Theis, and M. Bethge. Deep Gaze I: Boosting saliency prediction with feature maps trained on ImageNet. in ICLR Workshop, 2015.
34. G. Li and Y. Yu. Visual Saliency Based on Multiscale Deep Features. in CVPR, 2015.
35. L. Wang, H. Lu, X. Ruan, and M.-H. Yang. Deep Networks for Saliency Detection via Local Estimation and Global Search. in CVPR, 2015.
36. R. Zhao, W. Ouyang, H. Li, and X. Wang. Saliency detection by multi-context deep learning. in CVPR, 2015.
37. J. L. Long, N. Zhang, and T. Darrell. Do Convnets Learn Correspondence in NIPS, 2014.
38. C.-Y. Lee, S. Xie, P. Gallagher, Z. Zhang, and Z. Tu. Deeply-supervised nets. in AISTATS, 2015.
39. D. E. Rumelhart, G. E. Hinton, and R. J. Williams. Learning representations by back-propagating errors. Nature, 323 (6088): 533-538, 1986.
40. 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 ACM Multimedia, 2014.
41. W. Zhu, S. Liang, Y. Wei, and J. Sun. Saliency optimization from robust background detection. in CVPR, 2014.
42. L.-C. Chen, G. Papandreou, I. Kokkinos, K. Murphy, and A. L. Yuille. Semantic image segmentation with deep convolutional nets and fully connected CRFs. in ICLR, 2015.