[1] Kim J, Han D, Tai Y W, et al. Salient region detection via high-dimensional color transform and local spatial support[J]. IEEE Transactions on Image Processing, 2016, 25(1): 9-23.

    Kim J, Han D, Tai Y W, et al. Salient region detection via high-dimensional color transform and local spatial support[J]. IEEE Transactions on Image Processing, 2016, 25(1): 9-23.

[2] Cheng M M, Mitra N J, Huang X, et al. Global contrast based salient region detection[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015, 37(3): 569-582.

    Cheng M M, Mitra N J, Huang X, et al. Global contrast based salient region detection[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015, 37(3): 569-582.

[3] Zhu WJ, LiangS, Wei YC, et al. Saliency optimization from robust background detection[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2014: 2814- 2821.

    Zhu WJ, LiangS, Wei YC, et al. Saliency optimization from robust background detection[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2014: 2814- 2821.

[4] Jiang HZ, Wang JD, Yuan ZJ, et al. Salient object detection: a discriminative regional feature integration approach[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2013: 2083- 2090.

    Jiang HZ, Wang JD, Yuan ZJ, et al. Salient object detection: a discriminative regional feature integration approach[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2013: 2083- 2090.

[5] YanQ, XuL, Shi JP, et al. Hierarchical saliency detection[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2013: 1155- 1162.

    YanQ, XuL, Shi JP, et al. Hierarchical saliency detection[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2013: 1155- 1162.

[6] Liu RS, Cao JJ, Lin ZS, et al. Adaptive partial differential equation learning for visual saliency detection[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2014: 3866- 3873.

    Liu RS, Cao JJ, Lin ZS, et al. Adaptive partial differential equation learning for visual saliency detection[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2014: 3866- 3873.

[7] JiangP, VasconcelosN, Peng JL. Generic promotion of diffusion-based salient object detection[C]. IEEE International Conference on Computer Vision, 2015: 217- 225.

    JiangP, VasconcelosN, Peng JL. Generic promotion of diffusion-based salient object detection[C]. IEEE International Conference on Computer Vision, 2015: 217- 225.

[8] 刘大伟, 韩玲, 韩晓勇. 基于深度学习的高分辨率遥感影像分类研究[J]. 光学学报, 2016, 36(4): 0428001.

    刘大伟, 韩玲, 韩晓勇. 基于深度学习的高分辨率遥感影像分类研究[J]. 光学学报, 2016, 36(4): 0428001.

    Liu Dawei, Han Ling, Han Xiaoyong. High spatial resolution remote sensing imaging classification based on deep learning[J]. Acta Optica Sinica, 2016, 36(4): 0428001.

    Liu Dawei, Han Ling, Han Xiaoyong. High spatial resolution remote sensing imaging classification based on deep learning[J]. Acta Optica Sinica, 2016, 36(4): 0428001.

[9] GirshickR, DonahueJ, DarrellT, et al. Rich feature hierarchies for accurate object detection and semantic segmentation[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2014: 580- 587.

    GirshickR, DonahueJ, DarrellT, et al. Rich feature hierarchies for accurate object detection and semantic segmentation[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2014: 580- 587.

[10] TaigmanY, YangM, Ranzato MA, et al. Deepface: closing the gap to human-level performance in face verification[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2014: 1701- 1708.

    TaigmanY, YangM, Ranzato MA, et al. Deepface: closing the gap to human-level performance in face verification[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2014: 1701- 1708.

[11] Wang LJ, Lu HC, RuanX, et al. Deep networks for saliency detection via local estimation and global search[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2015: 3183- 3192.

    Wang LJ, Lu HC, RuanX, et al. Deep networks for saliency detection via local estimation and global search[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2015: 3183- 3192.

[12] LeeG, Tai YW, KimJ. Deep saliency with encoded low level distance map and high level features[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2016: 660- 668.

    LeeG, Tai YW, KimJ. Deep saliency with encoded low level distance map and high level features[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2016: 660- 668.

[13] LiuN, Han JW. DHSNet: deep hierarchical saliency network for salient object detection[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2016: 678- 686.

    LiuN, Han JW. DHSNet: deep hierarchical saliency network for salient object detection[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2016: 678- 686.

[14] Li GB, Yu YZ. Visual saliency based on multiscale deep features[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2015: 5455- 5463.

    Li GB, Yu YZ. Visual saliency based on multiscale deep features[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2015: 5455- 5463.

[15] ZhaoR, Ouyang WL, Li HS, et al. Saliency detection by multi-context deep learning[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2015: 1265- 1274.

    ZhaoR, Ouyang WL, Li HS, et al. Saliency detection by multi-context deep learning[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2015: 1265- 1274.

[16] 刘峰, 沈同圣, 韩艳丽, 等. 融合背景感知和颜色对比的显著性检测方法[J]. 计算机辅助设计与图形学学报, 2016, 28(10): 1705-1712.

    刘峰, 沈同圣, 韩艳丽, 等. 融合背景感知和颜色对比的显著性检测方法[J]. 计算机辅助设计与图形学学报, 2016, 28(10): 1705-1712.

    Liu Feng, Shen Tongsheng, Han Yanli, et al. Saliency detection via background aware and color contrast[J]. Journal of Computer-Aided Design & Computer Graphics, 2016, 28(10): 1705-1712.

    Liu Feng, Shen Tongsheng, Han Yanli, et al. Saliency detection via background aware and color contrast[J]. Journal of Computer-Aided Design & Computer Graphics, 2016, 28(10): 1705-1712.

[17] KrähenbühlP, KoltunV. Efficient inference in fully connected CRFs with Gaussian edge potentials[C]. Advances in Neural Information Processing Systems, 2011: 109- 117.

    KrähenbühlP, KoltunV. Efficient inference in fully connected CRFs with Gaussian edge potentials[C]. Advances in Neural Information Processing Systems, 2011: 109- 117.

[18] Jia YQ, ShelhamerE, DonahueJ, et al. Caffe: convolutional architecture for fast feature embedding[C]. 22nd ACM International Conference on Multimedia, ACM, 2014: 675- 678.

    Jia YQ, ShelhamerE, DonahueJ, et al. Caffe: convolutional architecture for fast feature embedding[C]. 22nd ACM International Conference on Multimedia, ACM, 2014: 675- 678.

[19] MargolinR, TalA, Zelnik-ManorL. What makes a patch distinct?[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2013: 1139- 1146.

    MargolinR, TalA, Zelnik-ManorL. What makes a patch distinct?[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2013: 1139- 1146.

[20] LiY, Hou XD, KochC, et al. The secrets of salient object segmentation[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2014: 280- 287.

    LiY, Hou XD, KochC, et al. The secrets of salient object segmentation[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2014: 280- 287.