Video salient object detection via self-attention-guided multilayer cross-stack fusion-Reference-Cited by-同舟云学术

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Video salient object detection via self-attention-guided multilayer cross-stack fusion

Published:2023-11-15 Issue: Volume: Page:
ISSN:1380-7501
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Yang Heng,Mu Nan^ORCID,Guo Jinjia,Hu Yiyue,Wang Rong

Funder

National Natural Science Foundation of China

National Youth Science Fund Project of Sichuan Province

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Link

https://link.springer.com/content/pdf/10.1007/s11042-023-17652-4.pdf

Reference34 articles.

1. Shafieyan F, Karimi N, Mirmahboub B, Samavi S, Shirani S (2014) Image seam carving using depth assisted saliency map. In: IEEE International Conference on Image Processing, pp. 1155–1159

2. Lee H, Kim D (2018) Salient region-based online object tracking. In: IEEE Winter Conference on Applications of Computer Vision, pp. 1170–1177

3. Wang L, Qiao Y, Tang X (2015) Action recognition with trajectory-pooled deep-convolutional descriptors. In: IEEE conference on computer vision and pattern recognition, pp. 4305–4314

4. Wang H, Kläser A, Schmid C, Liu C-L (2013) Dense trajectories and motion boundary descriptors for action recognition. Int J Comput Vision 103:60–79

5. Ji W, Yu S, Wu J, Ma K, Bian C, Bi Q, Li J, Liu H, Cheng L, Zheng Y (2021) Learning calibrated medical image segmentation via multi-rater agreement modeling. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 12341–12351

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