87 citations · 126 across the 14 of their papers we have counts for
15 papers
Learned Video Compression for YUV 4:2:0 Content Using Flow-based Conditional Inter-frame Coding
Yung-Han Ho, Chih-Hsuan Lin, Peng-Yu Chen +4
This paper proposes a learning-based video compression framework for variable-rate coding on YUV 4:2:0 content. Most existing learning-based video compression models adopt the trad…
OpenOOD: Benchmarking Generalized Out-of-Distribution Detection
Jingkang Yang, Pengyun Wang, Dejian Zou +13
Out-of-distribution (OOD) detection is vital to safety-critical machine learning applications and has thus been extensively studied, with a plethora of methods developed in the lit…
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…
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…
ANFIC: Image Compression Using Augmented Normalizing Flows
Yung-Han Ho, Chih-Chun Chan, Wen-Hsiao Peng +2
This paper introduces an end-to-end learned image compression system, termed ANFIC, based on Augmented Normalizing Flows (ANF). ANF is a new type of flow model, which stacks multip…
A Dual-Critic Reinforcement Learning Framework for Frame-level Bit Allocation in HEVC/H.265
Yung-Han Ho, Guo-Lun Jin, Yun Liang +2
This paper introduces a dual-critic reinforcement learning (RL) framework to address the problem of frame-level bit allocation in HEVC/H.265. The objective is to minimize the disto…