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In this paper, we propose a novel edge preserving and multi-scale contextual neural network for salient object detection.
L. Itti, C. Koch, and E. Niebur, “A model of saliency-based visual attention for rapid scene analysis,” IEEE TPAMI , 1998
1998
Earlier work this paper cites.
Y. Zhai and M. Shah, “Visual attention detection in video sequences using spatiotemporal cues,” in ACM MM , 2006
2006
Earlier work this paper cites.
T. Liu, J. Sun, N.-N. Zheng, X. Tang, and H.-Y. Shum, “Learning to detect a salient object,” in CVPR , 2007
2007
Earlier work this paper cites.
L. Zhang, M. H. Tong, T. K. Marks, H. Shan, and G. W. Cottrell, “Sun: A bayesian framework for saliency using natural statistics,” Journal of vision , vol. 8, no. 7, pp. 32–32, 2008
2008
Earlier work this paper cites.
V. Mahadevan and N. Vasconcelos, “Saliency-based discriminant tracking,” in Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on . IEEE, 2009, pp. 1007–1013
2009
Earlier work this paper cites.
R. Achanta, S. Hemami, F. Estrada, and S. Susstrunk, “Frequency-tuned salient region detection,” in CVPR , 2009
2009
Earlier work this paper cites.
N. Murray, M. Vanrell, X. Otazu, and C. A. Parraga, “Saliency estimation using a non-parametric low-level vision model,” in Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on . IEEE, 2011, pp. 433–440
2011
Earlier work this paper cites.
M.-M. Cheng, G.-X. Zhang, N. J. Mitra, X. Huang, and S.-M. Hu, “Global contrast based salient region detection,” in CVPR , 2011
2011
Earlier work this paper cites.
Y. Wei, F. Wen, W. Zhu, and J. Sun, “Geodesic saliency using background priors,” in ECCV , 2012
2012
Earlier work this paper cites.
R. Achanta, A. Shaji, K. Smith, A. Lucchi, P. Fua, and S. Susstrunk, “Slic superpixels compared to state-of-the-art superpixel methods,” IEEE TPAMI , 2012
2012
Earlier work this paper cites.
S. Alpert, M. Galun, A. Brandt, and R. Basri, “Image segmentation by probabilistic bottom-up aggregation and cue integration,” IEEE Transactions on Pattern Analysis and Machine Intelligence , vol. 34, no. 2, pp. 315–327, 2012
2012
Earlier work this paper cites.
F. Perazzi, P. Krähenbühl, Y. Pritch, and A. Hornung, “Saliency filters: Contrast based filtering for salient region detection,” in CVPR , 2012
2012
Earlier work this paper cites.
K. Shi, K. Wang, J. Lu, and L. Lin, “Pisa: pixelwise image saliency by aggregating complementary appearance contrast measures with spatial priors,” in CVPR , 2013
2013
Earlier work this paper cites.
P. Jiang, H. Ling, J. Yu, and J. Peng, “Salient region detection by ufo: Uniqueness, focusness and objectness,” in ICCV , 2013
2013
Earlier work this paper cites.
X. Li, Y. Li, C. Shen, A. Dick, and A. Van Den Hengel, “Contextual hypergraph modeling for salient object detection,” in Proceedings of the IEEE International Conference on Computer Vision , 2013, pp. 3328–3335
2013
Earlier work this paper cites.
Q. Yan, L. Xu, J. Shi, and J. Jia, “Hierarchical saliency detection,” in CVPR , 2013
2013
Earlier work this paper cites.
J. Zhang and S. Sclaroff, “Saliency detection: A boolean map approach,” in Proceedings of the IEEE international conference on computer vision , 2013, pp. 153–160
2013
Earlier work this paper cites.
P. Dollár and C. L. Zitnick, “Structured forests for fast edge detection,” in ICCV , 2013
2013
Earlier work this paper cites.
C. Yang, L. Zhang, H. Lu, X. Ruan, and M.-H. Yang, “Saliency detection via graph-based manifold ranking,” in CVPR , 2013
2013
Earlier work this paper cites.
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
2013
Earlier work this paper cites.
2014
Cited alongside, same era.
W. Zhu, S. Liang, Y. Wei, and J. Sun, “Saliency optimization from robust background detection,” in CVPR , 2014
2014
Cited alongside, same era.
J. Kim, D. Han, Y.-W. Tai, and J. Kim, “Salient region detection via high-dimensional color transform,” in CVPR , 2014
2014
Cited alongside, same era.
M. D. Zeiler and R. Fergus, “Visualizing and understanding convolutional networks,” in ECCV , 2014
2014
Cited alongside, same era.
R. Ju, L. Ge, W. Geng, T. Ren, and G. Wu, “Depth saliency based on anisotropic center-surround difference,” in 2014 IEEE International Conference on Image Processing (ICIP) . IEEE, 2014, pp. 1115–1119
2014
Cited alongside, same era.
J. Long, E. Shelhamer, and T. Darrell, “Fully convolutional networks for semantic segmentation,” in 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , 2015, pp. 3431–3440
2015
Later among the works it cites.
J. Ren, X. Gong, L. Yu, W. Zhou, and M. Y. Yang, “Exploiting global priors for RGB-D saliency detection,” in 2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) . IEEE, 2015, pp. 25–32
2015
Later among the works it cites.
B. Hariharan, P. Arbeláez, R. Girshick, and J. Malik, “Hypercolumns for object segmentation and fine-grained localization,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2015, pp. 447–456
2015
Later among the works it cites.
M. Liang and X. Hu, “Recurrent convolutional neural network for object recognition,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2015, pp. 3367–3375
2015
Later among the works it cites.
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H. Peng, B. Li, W. Xiong, W. Hu, and R. Ji, “Rgbd salient object detection: A benchmark and algorithms,” in European Conference on Computer Vision . Springer, 2014, pp. 92–109
2014
Cited alongside, same era.
2014
Cited alongside, same era.
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 MM , 2014
2014
Cited alongside, same era.
M.-M. Cheng, N. J. Mitra, X. Huang, and S.-M. Hu, “Salientshape: Group saliency in image collections,” The Visual Computer , vol. 30, no. 4, pp. 443–453, 2014
2014
Cited alongside, same era.
Y. Li, X. Hou, C. Koch, J. M. Rehg, and A. L. Yuille, “The secrets of salient object segmentation,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2014, pp. 280–287
2014
Cited alongside, same era.
Z. Liu, W. Zou, and O. Le Meur, “Saliency tree: A novel saliency detection framework,” IEEE TIP , 2014
2014
Cited alongside, same era.
2015
Cited alongside, same era.
S. Xie and Z. Tu, “Holistically-nested edge detection,” in ICCV , 2015
2015
Later among the works it cites.
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 International Conference on Learning Representations , 2015
2015
Later among the works it cites.
C.-Y. Lee, S. Xie, P. Gallagher, Z. Zhang, and Z. Tu, “Deeply-supervised nets.” in AISTATS , vol. 2, no. 3, 2015, p. 6
2015
Later among the works it cites.
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein et al. , “Imagenet large scale visual recognition challenge,” International Journal of Computer Vision , vol. 115, no. 3, pp. 211–252, 2015
2015
Later among the works it cites.
A. Borji, “What is a salient object? a dataset and a baseline model for salient object detection,” IEEE TIP , 2015
2015
Later among the works it cites.
A. Borji, M.-M. Cheng, H. Jiang, and J. Li, “Salient object detection: A benchmark,” IEEE Transactions on Image Processing , vol. 24, no. 12, pp. 5706–5722, 2015
2015
Later among the works it cites.
H. Li, H. Lu, Z. Lin, X. Shen, and B. Price, “Inner and inter label propagation: Salient object detection in the wild,” IEEE TIP , 2015
2015
Later among the works it cites.
J. Zhang, S. Sclaroff, Z. Lin, X. Shen, B. Price, and R. Mech, “Minimum barrier salient object detection at 80 fps,” in ICCV , 2015
2015
Later among the works it cites.
T. Chen, L. Lin, L. Liu, X. Luo, and X. Li, “DISC: Deep image saliency computing via progressive representation learning,” IEEE TNNLS , 2016
2016
Closest in time.
X. Li, L. Zhao, L. Wei, M. Yang, F. Wu, Y. Zhuang, H. Ling, and J. Wang, “Deepsaliency: Multi-task deep neural network model for salient object detection,” IEEE Transactions on Image Processing , vol. 25, no. 8, pp. 3919–3930, 2016
2016
Closest in time.
Y. Li, J. Yosinski, J. Clune, H. Lipson, and J. Hopcroft, “Convergent learning: Do different neural networks learn the same representations?” in ICLR , 2016
2016
Closest in time.
D. Feng, N. Barnes, S. You, and C. McCarthy, “Local background enclosure for RGB-D salient object detection,” in 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) . IEEE, 2016
2016
Closest in time.
N. Liu and J. Han, “DHSNet: Deep hierarchical saliency network for salient object detection,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2016, pp. 678–686
2016
Closest in time.
X. Wang, H. Ma, and X. Chen, “Salient object detection via Fast R-CNN and low-level cues,” in IEEE ICIP , 2016
2016
Closest in time.
J. Dai, K. He, and J. Sun, “Instance-aware semantic segmentation via multi-task network cascades,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2016, pp. 3150–3158
2016
Closest in time.