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Computer Science

D-Index
51
Citations
29706
World Ranking
5194
National Ranking
2383

Overview

Ming-Yu Liu is affiliated with Nvidia in the United States and has contributed extensively to the field of computer science, with a notable focus on computer vision and pattern recognition. Their body of work spans various subfields including artificial intelligence, computer networks and communications, computer graphics and computer-aided design, and information systems.

The scientist's recent publications reflect a broad engagement with topics such as generative adversarial networks and image synthesis, advanced vision and imaging, natural language processing techniques, multimodal machine learning applications, computer graphics and visualization techniques, handwritten text recognition techniques, and topic modeling.

  • eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers (2022) - arXiv (Cornell University)
  • Video-to-Video Synthesis (2025) - arXiv (Cornell University)
  • GANcraft: Unsupervised 3D Neural Rendering of Minecraft Worlds (2021) - 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Lens aberration compensation in interference microscopy (2020) - Optics and Lasers in Engineering
  • Learning to Relight Portrait Images via a Virtual Light Stage and Synthetic-to-Real Adaptation (2022) - ACM Transactions on Graphics

Their research has been predominantly disseminated through the following venues:

  • arXiv (Cornell University)
  • Neurocomputing
  • SSRN Electronic Journal
  • Zenodo (CERN European Organization for Nuclear Research)
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Ming-Yu Liu frequently collaborates with several other researchers in the field. Among the most frequent co-authors are Ting-Chun Wang, Arun Mallya, Jan Kautz, Li Pan, and Shijun Liu.

  • Ting-Chun Wang
  • Arun Mallya
  • Jan Kautz
  • Li Pan
  • Shijun Liu

Their contributions to computer science include a substantial number of publications centered on computer vision and artificial intelligence topics, indicating an emphasis on both theoretical aspects and practical applications of advanced imaging, synthesis, and machine learning techniques.

Best Publications

  • High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs

    Ting-Chun Wang;Ming-Yu Liu;Jun-Yan Zhu;Andrew Tao

  • Semantic Image Synthesis With Spatially-Adaptive Normalization

    Taesung Park;Ming-Yu Liu;Ting-Chun Wang;Jun-Yan Zhu

  • Multimodal Unsupervised Image-to-Image Translation

    Xun Huang;Ming-Yu Liu;Serge J. Belongie;Jan Kautz

  • PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume

    Deqing Sun;Xiaodong Yang;Ming-Yu Liu;Jan Kautz

  • Unsupervised Image-to-Image Translation Networks

    Ming-Yu Liu;Thomas M. Breuel;Jan Kautz

  • Coupled Generative Adversarial Networks

    Ming-Yu Liu;Oncel Tuzel

  • Entropy rate superpixel segmentation

    Ming-Yu Liu;Oncel Tuzel;Srikumar Ramalingam;Rama Chellappa

  • Magic3D: High-Resolution Text-to-3D Content Creation

    Unknown

  • MoCoGAN: Decomposing Motion and Content for Video Generation

    Sergey Tulyakov;Ming-Yu Liu;Xiaodong Yang;Jan Kautz

  • Few-Shot Unsupervised Image-to-Image Translation

    Ming-Yu Liu;Xun Huang;Arun Mallya;Tero Karras

  • PointFlow: 3D Point Cloud Generation With Continuous Normalizing Flows

    Guandao Yang;Xun Huang;Zekun Hao;Ming-Yu Liu

  • Video-to-Video Synthesis

    Ting-Chun Wang;Ming-Yu Liu;Jun-Yan Zhu;Guilin Liu

  • CityFlow: A City-Scale Benchmark for Multi-Target Multi-Camera Vehicle Tracking and Re-Identification

    Zheng Tang;Milind Naphade;Ming-Yu Liu;Xiaodong Yang

  • A Closed-Form Solution to Photorealistic Image Stylization

    Yijun Li;Ming Yu Liu;Xueting Li;Ming Hsuan Yang

  • One-Shot Free-View Neural Talking-Head Synthesis for Video Conferencing

    Ting-Chun Wang;Arun Mallya;Ming-Yu Liu

  • R-CNN for Small Object Detection

    Chenyi Chen;Ming-Yu Liu;Oncel Tuzel;Jianxiong Xiao

  • Tactics of Adversarial Attack on Deep Reinforcement Learning Agents.

    Yen-Chen Lin;Zhang-Wei Hong;Yuan-Hong Liao;Meng-Li Shih

  • CASENet: Deep Category-Aware Semantic Edge Detection

    Zhiding Yu;Chen Feng;Ming-Yu Liu;Srikumar Ramalingam

  • Superpixel sampling networks

    Varun Jampani;Deqing Sun;Ming Yu Liu;Ming Hsuan Yang

  • Joint Geodesic Upsampling of Depth Images

    Ming-Yu Liu;Oncel Tuzel;Yuichi Taguchi

  • Fast directional chamfer matching

    Ming-Yu Liu;Oncel Tuzel;Ashok Veeraraghavan;Rama Chellappa

  • Few-shot Video-to-Video Synthesis

    Ting-Chun Wang;Ming-Yu Liu;Andrew Tao;Guilin Liu

Frequent Co-Authors

Jan Kautz
Jan Kautz Nvidia (United States)
Oncel Tuzel
Oncel Tuzel Apple (United States)
Xiaodong Yang
Xiaodong Yang Nvidia (United Kingdom)
Ming-Hsuan Yang
Ming-Hsuan Yang University of California, Merced
Deqing Sun
Deqing Sun Google (United States)
Rama Chellappa
Rama Chellappa Johns Hopkins University
Min Sun
Min Sun National Tsing Hua University
Jinwei Gu
Jinwei Gu Chinese University of Hong Kong
Jun-Yan Zhu
Jun-Yan Zhu Carnegie Mellon University

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