Semantic Co-segmentation in Videos-Reference-Cited by-同舟云学术

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Semantic Co-segmentation in Videos

Published:2016 Issue: Volume: Page:760-775
ISSN:0302-9743
Container-title:Computer Vision – ECCV 2016
language:
Short-container-title:

Author:

Tsai Yi-Hsuan,Zhong Guangyu,Yang Ming-Hsuan

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-46493-0_46

Reference36 articles.

1. Boykov, Y., Kolmogorov, V.: An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision. PAMI 26(9), 1124–1137 (2004)

2. Chen, X., Shrivastava, A., Gupta, A.: Enriching visual knowledge bases via object discovery and segmentation. In: CVPR (2014)

3. Chiu, W.C., Fritz, M.: Multi-class video co-segmentation with a generative multi-video model. In: CVPR (2013)

4. Cho, M., Kwak, S., Schmid, C., Ponce, J.: Unsupervised object discovery and localization in the wild: Part-based matching with bottom-up region proposals. In: CVPR (2015)

5. Everingham, M., Gool, L.J.V., Williams, C.K.I., Winn, J.M., Zisserman, A.: The pascal visual object classes (VOC) challenge. IJCV 88(2), 303–338 (2010)

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1. Motion perception-driven multimodal self-supervised video object segmentation;The Visual Computer;2024-08-09

2. Adaptive Multi-Source Predictor for Zero-Shot Video Object Segmentation;International Journal of Computer Vision;2024-03-07

3. VOS;Video Object Segmentation;2023-12-16

4. Mask-Free Video Instance Segmentation;2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR);2023-06

5. TCAM: Temporal Class Activation Maps for Object Localization in Weakly-Labeled Unconstrained Videos;2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV);2023-01

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