B. Qin, Z. Gu, X. Sun, and Y. Lv, Registration of images with outliers using joint saliency map, IEEE Signal Process. Lett, vol.17, issue.1, pp.91-94, 2010.

B. Qin, Z. Shen, Z. Fu, Z. Zhou, Y. Lv et al., Joint-saliency structure adaptive kernel regression with adaptive-scale kernels for deformable regis-485 tration of challenging images, IEEE Access, vol.6, pp.330-343, 2018.

X. Zhi and H. Shen, Saliency driven region-edge-based top down level set evolution reveals the asynchronous focus in image segmentation, Pattern Recognition, vol.80, pp.241-255, 2018.

W. Wang, J. Shen, R. Yang, and F. Porikli, Saliency-aware video object seg-490 mentation, IEEE Trans. Pattern Anal. Mach. Intell, vol.40, issue.1, pp.20-33, 2018.

Z. Zhao, B. Zhao, and F. Su, Person re-identification via integrating patchbased metric learning and local salience learning, Pattern Recognition, vol.75, pp.90-98, 2018.

W. Xie, Y. Shi, Y. Li, X. Jia, and J. Lei, High-quality spectral-spatial recon-495 struction using saliency detection and deep feature enhancement, Pattern Recognition, vol.88, pp.139-152, 2019.

A. Borji, M. Cheng, H. Jiang, and J. Li, Salient object detection: A survey

W. Tu, S. He, Q. Yang, and S. Chien, Real-time salient object detection with 500 a minimum spanning tree, 2016 IEEE Conference on Computer Vision and Pattern Recognition, pp.2334-2342, 2016.

J. Zhang, S. Sclaroff, Z. L. Lin, X. Shen, B. L. Price et al., Minimum barrier salient object detection at 80 FPS, IEEE International, p.505, 2015.

B. Jiang, L. Zhang, H. Lu, C. Yang, and M. Yang, Saliency detection via absorbing markov chain, 2013 IEEE International Conference on Computer Vision, ICCV 2013, vol.510, pp.1665-1672, 2013.

H. Kim, Y. Kim, J. Sim, and C. Kim, Spatiotemporal saliency detection for video sequences based on random walk with restart, IEEE Trans. Image Processing, vol.24, issue.8, pp.2552-2564, 2015.

W. Wang, J. Shen, and L. Shao, Consistent video saliency using local gradient 515 flow optimization and global refinement, IEEE Trans. Image Processing, vol.24, issue.11, pp.4185-4196, 2015.

Z. Liu, J. Li, L. Ye, G. Sun, and L. Shen, Saliency detection for unconstrained videos using superpixel-level graph and spatiotemporal propagation, IEEE Trans. Circuits Syst. Video Techn, vol.27, issue.12, pp.2527-2542, 2017.

K. He, J. Sun, and X. Tang, Computer Vision -ECCV 2010, 11th European Conference on Computer Vision, pp.1-14, 2010.

D. Shan, X. Zhang, and C. Zhang, Visual saliency based on extended manifold ranking and third-order optimization refinement, Pattern Recognition, vol.525, pp.1-7, 2018.

X. Huang and Y. Zhang, Water flow driven salient object detection at 180 fps, Pattern Recognition, vol.76, pp.95-107, 2018.

M. M. Lie, G. B. Borba, H. V. Neto, and H. R. Gamba, Joint upsampling of random color distance maps for fast salient region detection, vol.114, pp.22-30, 2018.

Ç. Aytekin, A. Iosifidis, and M. Gabbouj, Probabilistic saliency estimation, Pattern Recognition, vol.74, pp.359-372, 2018.

X. Li, H. Ma, X. Wang, and K. Zhang, Saliency detection via alternative optimization adaptive influence matrix model, Pattern Recognition Letters, vol.101, pp.29-36, 2018.

Y. Yan, J. Ren, G. Sun, H. Zhao, J. Han et al., Unsupervised image saliency detection with gestalt-laws guided optimization and visual attention based refinement, Pattern Recognition, vol.79, pp.65-78, 2018.

H. Peng, B. Li, H. Ling, W. Hu, W. Xiong et al., Salient object detection via structured matrix decomposition, IEEE Trans. Pattern Anal. Mach. Intell, vol.39, issue.4, pp.818-832, 2017.

Q. Wang, L. Zhang, and K. Kpalma, Fast filtering-based temporal saliency detection using minimum barrier distance, 2017 IEEE International 545 Conference on Multimedia & Expo Workshops, ICME Workshops
URL : https://hal.archives-ouvertes.fr/hal-01637078

C. Kong, , pp.232-237, 2017.

S. Bhattacharya, V. K. Subramanian, and S. Gupta, Visual saliency detection using spatiotemporal decomposition, IEEE Trans. Image Processing, vol.27, issue.4, pp.1665-1675, 2018.

Z. Tu, Z. Guo, W. Xie, M. Yan, R. C. Veltkamp et al., Fusing disparate object signatures for salient object detection in video, Pattern Recognition, vol.72, pp.285-299, 2017.

B. Yang, X. Zhang, L. Chen, and Z. Gao, Spatiotemporal salient object detection based on distance transform and energy optimization, Neurocomputing, vol.555, pp.165-175, 2017.

J. Li, C. Xia, and X. Chen, A benchmark dataset and saliency-guided stacked autoencoders for video-based salient object detection, IEEE Trans. Image Processing, vol.27, issue.1, pp.349-364, 2018.

C. Chen, Y. Li, S. Li, H. Qin, and A. Hao, A novel bottom-up saliency detection 560 method for video with dynamic background, IEEE Signal Process. Lett, vol.25, issue.2, pp.154-158, 2018.

W. Wang, J. Shen, and F. Porikli, Saliency-aware geodesic video object segmentation, IEEE Conference on Computer Vision and Pattern Recognition, pp.3395-3402, 2015.

T. Xi, W. Zhao, H. Wang, and W. Lin, Salient object detection with spatiotemporal background priors for video, IEEE Trans. Image Processing, vol.26, issue.7, pp.3425-3436, 2017.

X. Zhou, Z. Liu, C. Gong, and W. Liu, Improving video saliency detection via localized estimation and spatiotemporal refinement, IEEE Trans. Multime, vol.570, issue.20, pp.2993-3007, 2018.

Y. Chen, W. Zou, Y. Tang, X. Li, C. Xu et al., SCOM: spatiotemporal constrained optimization for salient object detection, IEEE Trans. Image Processing, vol.27, issue.7, pp.3345-3357, 2018.

H. Ramadan and H. Tairi, Pattern mining-based video saliency detection: Ap-575 plication to moving object segmentation, Computers & Electrical Engineering, vol.70, pp.567-579, 2018.

F. Guo, W. Wang, J. Shen, L. Shao, J. Yang et al., Video saliency detection using object proposals, IEEE Trans. Cybernetics, vol.48, issue.11, pp.3159-3170, 2018.

C. Chen, S. Li, Y. Wang, H. Qin, and A. Hao, Video saliency detection via spatial-temporal fusion and low-rank coherency diffusion, IEEE Trans. Image Processing, vol.26, issue.7, pp.3156-3170, 2017.

C. Chen, S. Li, H. Qin, Z. Pan, and G. Yang, Bilevel feature learning for video saliency detection, IEEE Trans. Multimedia, vol.20, issue.12, pp.3324-3336, 2018.

N. Liu and J. Han, Dhsnet: Deep hierarchical saliency network for salient object detection, 2016 IEEE Conference on Computer Vision and Pattern Recognition, pp.678-686, 2016.

Q. Hou, M. Cheng, X. Hu, A. Borji, Z. Tu et al., Deeply supervised 590 salient object detection with short connections, 2017 IEEE Conference on Computer Vision and Pattern Recognition, pp.5300-5309, 2017.

G. Lee, Y. Tai, and J. Kim, Eld-net: An efficient deep learning architecture for accurate saliency detection, IEEE Trans. Pattern Anal. Mach. Intell, vol.40, issue.7, pp.1599-1610, 2018.

H. Chen, Y. Li, and D. Su, Multi-modal fusion network with multi-scale multipath and cross-modal interactions for RGB-D salient object detection, vol.86, pp.376-385, 2019.

Q. Yuan, Y. Wei, X. Meng, H. Shen, and L. Zhang, A multiscale and multidepth 600 convolutional neural network for remote sensing imagery pan-sharpening

. Ieee-j-sel, Topics in Appl. Earth Observ. and Remote Sensing, vol.11, issue.3, pp.978-989, 2018.

W. Wang, J. Shen, and L. Shao, Video salient object detection via fully convolutional networks, IEEE Trans. Image Processing, vol.27, issue.1, pp.38-49, 2018.

Y. Tang, W. Zou, Z. Jin, Y. Chen, Y. Hua et al., Weakly supervised salient object detection with spatiotemporal cascade neural networks, IEEE Trans. Circuits Syst. Video Techn, 2018.

Y. Hu, R. Song, and Y. Li, Efficient coarse-to-fine patch match for large displacement optical flow, p.610, 2016.

, Pattern Recognition, pp.5704-5712, 2016.

K. Fukuchi, K. Miyazato, A. Kimura, S. Takagi, and J. Yamato, Saliency-based video segmentation with graph cuts and sequentially updated priors, Proceedings of the 2009 IEEE International Conference on Multimedia and, p.615

A. Borji, M. Cheng, H. Jiang, and J. Li, Salient object detection: A benchmark, IEEE Trans. Image Processing, vol.24, issue.12, pp.5706-5722, 2015.

, Qiong Wang received the Ph.D. degree from the

, Applied Sciences of Rennes" in France, 2019.

, Her current research interests include visual saliency detection, video object segmentation, and deep learning

, Angers, p.625

. France, She is currently an Associate Professor in the "National Institute of Applied Sciences of Rennes" in France. Her research interests include visual saliency detection, multimedia quality assessment, medical imaging and human perception understanding, 2012.

, Wenbin ZOU received the Ph.D. degree from the "National Institute of 630

, Since 2015, he has been with the faculty of the College of Information Engineering, 2014.