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TCGL: Temporal Contrastive Graph for Self-supervised Video Representation Learning


Jan 05, 2022
Yang Liu, Keze Wang, Lingbo Liu, Haoyuan Lan, Liang Lin

* This work has been submitted to the IEEE for possible publication. The code is publicly available at https://github.com/YangLiu9208/TCGL. arXiv admin note: substantial text overlap with arXiv:2101.00820 

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Enhancing Prototypical Few-Shot Learning by Leveraging the Local-Level Strategy


Nov 08, 2021
Junying Huang, Fan Chen, Keze Wang, Liang Lin, Dongyu Zhang

* 5 pages, 4 figures, submitted to ICASSP 2022 

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CX-ToM: Counterfactual Explanations with Theory-of-Mind for Enhancing Human Trust in Image Recognition Models


Sep 06, 2021
Arjun R. Akula, Keze Wang, Changsong Liu, Sari Saba-Sadiya, Hongjing Lu, Sinisa Todorovic, Joyce Chai, Song-Chun Zhu

* Accepted by iScience Cell Press Journal 2021. arXiv admin note: text overlap with arXiv:1909.06907 

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Solving Inefficiency of Self-supervised Representation Learning


Apr 18, 2021
Guangrun Wang, Keze Wang, Guangcong Wang, Phillip H. S. Torr, Liang Lin

* 11 pages, 3 figures 

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Temporal Contrastive Graph for Self-supervised Video Representation Learning


Feb 01, 2021
Yang Liu, Keze Wang, Haoyuan Lan, Liang Lin

* 11 pages, 4 figures 

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Knowledge-Routed Visual Question Reasoning: Challenges for Deep Representation Embedding


Dec 14, 2020
Qingxing Cao, Bailin Li, Xiaodan Liang, Keze Wang, Liang Lin

* To appear in TNNLS 2021. Considering that a desirable VQA model should correctly perceive the image context, understand the question, and incorporate its learned knowledge, our proposed dataset aims to cutoff the shortcut learning exploited by the current deep embedding models and push the research boundary of the knowledge-based visual question reasoning 

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Continuous Transition: Improving Sample Efficiency for Continuous Control Problems via MixUp


Nov 30, 2020
Junfan Lin, Zhongzhan Huang, Keze Wang, Xiaodan Liang, Weiwei Chen, Liang Lin


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