5 papers
Leveraging Second-Order Curvature for Efficient Learned Image Compression: Theory and Empirical Evidence
Yichi Zhang, Fengqing Zhu
Training learned image compression (LIC) models entails navigating a challenging optimization landscape defined by the fundamental trade-off between rate and distortion. Standard f…
OpenDCVCs: A PyTorch Open Source Implementation and Performance Evaluation of the DCVC series Video Codecs
Yichi Zhang, Fengqing Zhu
We present OpenDCVCs, an open-source PyTorch implementation designed to advance reproducible research in learned video compression. OpenDCVCs provides unified and training-ready im…
Low-Rank Adaptation of Pre-trained Vision Backbones for Energy-Efficient Image Coding for Machine
Yichi Zhang, Zhihao Duan, Yuning Huang +1
Image Coding for Machines (ICM) focuses on optimizing image compression for AI-driven analysis rather than human perception. Existing ICM frameworks often rely on separate codecs f…
Accelerating Learned Image Compression Through Modeling Neural Training Dynamics
Yichi Zhang, Zhihao Duan, Yuning Huang +1
As learned image compression (LIC) methods become increasingly computationally demanding, enhancing their training efficiency is crucial. This paper takes a step forward in acceler…
Balanced Rate-Distortion Optimization in Learned Image Compression
Yichi Zhang, Zhihao Duan, Yuning Huang +1
Learned image compression (LIC) using deep learning architectures has seen significant advancements, yet standard rate-distortion (R-D) optimization often encounters imbalanced upd…