De-blocking Filter Design for HEVC and H.264/AVC. - Muchen Li; Jinjia Zhou; Dajiang Zhou; Xiao Peng 002; Satoshi Goto (PCM, 2012)

Low-complexity merge candidate decision for fast HEVC encoding. - Muchen Li; Keiichi Chono; Satoshi Goto (ICME Workshops, 2013)

A Dual-Mode Deblocking Filter Design for HEVC and H.264/AVC. - Muchen Li; Jinjia Zhou; Dajiang Zhou; Xiao Peng 002; Satoshi Goto (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2013)

Collective Strategies with a Master-slave Mechanism Dominate in Spatial Iterated Prisoner's Dilemma. - Jiawei Li 001; Jingpeng Li 001; Ruibin Bai; Robert Duncan; Muchen Li; Graham Kendall (CoRR, 2018)

Learning Deformable Kernels for Image and Video Denoising. - Xiangyu Xu 002; Muchen Li; Wenxiu Sun (CoRR, 2019)

NTIRE 2020 Challenge on Video Quality Mapping: Methods and Results. - Dario Fuoli; Zhiwu Huang; Martin Danelljan; Radu Timofte; Hua Wang 015; Longcun Jin; Dewei Su; Jing Liu 031; Jaehoon Lee; Michal Kudelski; Lukasz Bala; Dmitry Hrybov; et al. (CVPR Workshops, 2020)

SR-CL-DMC: P-frame coding with Super-Resolution, Color Learning, and Deep Motion Compensation. - Man M. Ho; Jinjia Zhou; Gang He 002; Muchen Li; Lei Li (CVPR Workshops, 2020)

TubeTK: Adopting Tubes to Track Multi-Object in a One-Step Training Model. - Bo Pang 003; Yizhuo Li 001; Yifan Zhang; Muchen Li; Cewu Lu (CVPR, 2020)

High-speed Compressed Sensing Reconstruction using Zigzag Ordering based Parallel Processing. - Jiayao Xu; Jirayu Peetakul; Muchen Li; Jinjia Zhou (ICVIP, 2020)

Learning Spatial and Spatio-Temporal Pixel Aggregations for Image and Video Denoising. - Xiangyu Xu 002; Muchen Li; Wenxiu Sun; Ming-Hsuan Yang 001 (IEEE Trans. Image Process., 2020)

TDAF: Top-Down Attention Framework for Vision Tasks. - Bo Pang 003; Yizhuo Li 001; Jiefeng Li; Muchen Li; Hanwen Cao; Cewu Lu (AAAI, 2021)

Referring Transformer: A One-step Approach to Multi-task Visual Grounding. - Muchen Li; Leonid Sigal (NeurIPS, 2021)

GraphPNAS: Learning Distribution of Good Neural Architectures via Deep Graph Generative Models. - Muchen Li; Jeffrey Yunfan Liu; Leonid Sigal; Renjie Liao (CoRR, 2022)

GraphPNAS: Learning Probabilistic Graph Generators for Neural Architecture Search. - Muchen Li; Jeffrey Yunfan Liu; Leonid Sigal; Renjie Liao (Trans. Mach. Learn. Res., 2023)

Learning Latent Structures in Network Games via Data-Dependent Gated-Prior Graph Variational Autoencoders. - Xue Yu; Muchen Li; Yan Leng; Renjie Liao (ICML, 2024)

LatentHOI: On the Generalizable Hand Object Motion Generation with Latent Hand Diffusion. - Muchen Li; Sammy Christen; Chengde Wan; Yujun Cai; Renjie Liao; Leonid Sigal; Shugao Ma (CVPR, 2025)

Leveraging Online Olympiad-Level Math Problems for LLMs Training and Contamination-Resistant Evaluation. - Sadegh Mahdavi; Muchen Li; Kaiwen Liu; Christos Thrampoulidis; Leonid Sigal; Renjie Liao (CoRR, 2025)

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization. - Wenlong Deng; Yi Ren; Muchen Li; Danica J. Sutherland; Xiaoxiao Li; Christos Thrampoulidis (CoRR, 2025)

Driver Assistant: Persuading Drivers to Adjust Secondary Tasks Using Large Language Models. - Wei Xiang; Muchen Li; Jie Yan; Manling Zheng; Hanfei Zhu; Mengyun Jiang; Lingyun Sun (CoRR, 2025)