Enhanced Motion Compensation for Deep Video Compression
Author:
Affiliation:
1. Department of Computer Science, City University of Hong Kong, Hong Kong
2. Wangxuan Institute of Computer Technology, Peking University, Beijing, China
Funder
Ministry of Science and Technology of China
Key Project of Science and Technology Innovation 2030
Hong Kong Innovation and Technology Commission
Hong Kong GRFRGC General Research Fund
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Applied Mathematics,Electrical and Electronic Engineering,Signal Processing
Link
http://xplorestaging.ieee.org/ielx7/97/10036333/10128699.pdf?arnumber=10128699
Reference34 articles.
1. Temporal context mining for learned video compression;sheng,2021
2. Deep contextual video compression;li;Proc Adv Neural Inf Process Syst,0
3. DMVC: Decomposed Motion Modeling for Learned Video Compression
4. Scale-Space Flow for End-to-End Optimized Video Compression
5. Hybrid Spatial-Temporal Entropy Modelling for Neural Video Compression
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2. Cross-Frame Integrated Prediction for Feature-Space Video Compression;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30
3. PFR-VC: Learning-Based Video Compression Framework with Predicted Frame Refinement;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30
4. LVC-LGMC: Joint Local and Global Motion Compensation for Learned Video Compression;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14
5. Multi-Scale Motion Alignment and Frame Reconstruction for Efficient Deep Video Compression;IEEE Signal Processing Letters;2024
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