activity
20222026
most citedAction-Constrained Reinforcement Learning for Frame-Level Bit Allocation in HEVC/H.265 through Frank-Wolfe Policy Optimization

1 citations · 1 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2026

CSGaussian: Progressive Rate-Distortion Compression and Segmentation for 3D Gaussian Splatting

Yu-Jen Tseng, Chia-Hao Kao, Jing-Zhong Chen +4

We present the first unified framework for rate-distortion-optimized compression and segmentation of 3D Gaussian Splatting (3DGS). While 3DGS has proven effective for both real-tim…

eess.IV2024

Learning Optimal Linear Block Transform by Rate Distortion Minimization

Alessandro Gnutti, Chia-Hao Kao, Wen-Hsiao Peng +1

Linear block transform coding remains a fundamental component of image and video compression. Although the Discrete Cosine Transform (DCT) is widely employed in all current compres…

cs.CV2024

Bridging Compressed Image Latents and Multimodal Large Language Models

Chia-Hao Kao, Cheng Chien, Yu-Jen Tseng +5

This paper presents the first-ever study of adapting compressed image latents to suit the needs of downstream vision tasks that adopt Multimodal Large Language Models (MLLMs). MLLM…

cs.CV2023

Transformer-based Image Compression with Variable Image Quality Objectives

Chia-Hao Kao, Yi-Hsin Chen, Cheng Chien +2

This paper presents a Transformer-based image compression system that allows for a variable image quality objective according to the user's preference. Optimizing a learned codec f…

eess.IV2023

TransTIC: Transferring Transformer-based Image Compression from Human Perception to Machine Perception

Yi-Hsin Chen, Ying-Chieh Weng, Chia-Hao Kao +3

This work aims for transferring a Transformer-based image compression codec from human perception to machine perception without fine-tuning the codec. We propose a transferable Tra…

eess.IV2023

Transformer-based Variable-rate Image Compression with Region-of-interest Control

Chia-Hao Kao, Ying-Chieh Weng, Yi-Hsin Chen +2

This paper proposes a transformer-based learned image compression system. It is capable of achieving variable-rate compression with a single model while supporting the region-of-in…

eess.IV2022

Neural Frank-Wolfe Policy Optimization for Region-of-Interest Intra-Frame Coding with HEVC/H.265

Yung-Han Ho, Chia-Hao Kao, Wen-Hsiao Peng +1

This paper presents a reinforcement learning (RL) framework that utilizes Frank-Wolfe policy optimization to solve Coding-Tree-Unit (CTU) bit allocation for Region-of-Interest (ROI…

eess.IV2022★ 1 cited

Action-Constrained Reinforcement Learning for Frame-Level Bit Allocation in HEVC/H.265 through Frank-Wolfe Policy Optimization

Yung-Han Ho, Yun Liang, Chia-Hao Kao +1

This paper presents a reinforcement learning (RL) framework that leverages Frank-Wolfe policy optimization to address frame-level bit allocation for HEVC/H.265. Most previous RL-ba…