Reinforcement Learning based ROI Bit Allocation for Gaming Video Coding in VVC
Author:
Funder
Tencent
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9675283/9675313/09675345.pdf?arnumber=9675345
Reference24 articles.
1. Efficient bit allocation and CTU level rate control for High Efficiency Video Coding
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4. Region-of-interest-based rate control scheme for high-efficiency video coding
5. A novel weight-based URQ scheme for perceptual video coding of conversational video in HEVC
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1. Rate Control Optimizing Model for Constraining Over-Saturated Live Streaming Quality;2024 IEEE International Conference on Multimedia and Expo Workshops (ICMEW);2024-07-15
2. Multi-Agent Reinforcement Learning based Bit Allocation for Gaming Video Coding;2024 Picture Coding Symposium (PCS);2024-06-12
3. Video Rate Controller Development Through Neuro-Fuzzy Quantization Parameter Modifiers;Journal of Signal Processing Systems;2023-06
4. Neural Frank-Wolfe Policy Optimization for Region-of-Interest Intra-Frame Coding with HEVC/H.265;2022 IEEE International Conference on Visual Communications and Image Processing (VCIP);2022-12-13
5. Rate Control Technology for Next Generation Video Coding Overview and Future Perspective;Electronics;2022-12-06
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