92 citations · 223 across the 25 of their papers we have counts for
6 papers · 1 filter
Adaptive Rate Control for Deep Video Compression with Rate-Distortion Prediction
Bowen Gu, Hao Chen, Ming Lu +2
Deep video compression has made significant progress in recent years, achieving rate-distortion performance that surpasses that of traditional video compression methods. However, r…
High-Efficiency Neural Video Compression via Hierarchical Predictive Learning
Ming Lu, Zhihao Duan, Wuyang Cong +3
The enhanced Deep Hierarchical Video Compression-DHVC 2.0-has been introduced. This single-model neural video codec operates across a broad range of bitrates, delivering not only s…
All-in-One Image Coding for Joint Human-Machine Vision with Multi-Path Aggregation
Xu Zhang, Peiyao Guo, Ming Lu +1
Image coding for multi-task applications, catering to both human perception and machine vision, has been extensively investigated. Existing methods often rely on multiple task-spec…
Accelerating block-level rate control for learned image compression
Muchen Dong, Ming Lu, Zhan Ma
Despite the unprecedented compression efficiency achieved by deep learned image compression (LIC), existing methods usually approximate the desired bitrate by adjusting a single qu…
Towards Backward-Compatible Continual Learning of Image Compression
Zhihao Duan, Ming Lu, Justin Yang +3
This paper explores the possibility of extending the capability of pre-trained neural image compressors (e.g., adapting to new data or target bitrates) without breaking backward co…
Another Way to the Top: Exploit Contextual Clustering in Learned Image Coding
Yichi Zhang, Zhihao Duan, Ming Lu +3
While convolution and self-attention are extensively used in learned image compression (LIC) for transform coding, this paper proposes an alternative called Contextual Clustering b…