CLSA: A Contrastive Learning Framework With Selective Aggregation for Video Rescaling

Author:

Tian Yuan1ORCID,Yan Yichao2ORCID,Zhai Guangtao2ORCID,Chen Li2ORCID,Gao Zhiyong2

Affiliation:

1. MoE Key Laboratory of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University, Shanghai, China

2. Institute of Image Communication and Network Engineering, Shanghai Jiao Tong University, Shanghai, China

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Shanghai Municipal Science and Technology Major Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Software

Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Coding Framework and Benchmark Towards Low-Bitrate Video Understanding;IEEE Transactions on Pattern Analysis and Machine Intelligence;2024-08

2. Context-guided Resolution Rescaling Framework for Intra Frame Coding;2024 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB);2024-06-19

3. Towards Omniscient Feature Alignment for Video Rescaling;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

4. Semantics-Guided and Saliency-Focused Learning of Perceptual Video Compression;IEEE Access;2024

5. MAS-CL: An End-to-End Multi-Atlas Supervised Contrastive Learning Framework for Brain ROI Segmentation;IEEE Transactions on Image Processing;2024

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