Ming-Yu Liu is a researcher at Nvidia Research. Prior to joining NVIDIA, he was a researcher at Mitsubishi Electric Research Labs (MERL). He received his Ph.D. from the Department of Electrical and Computer Engineering at the University of Maryland College Park in 2012. His research interests are on computer vision and deep learning. His early research work on object pose estimation contributed to development of the first commercial vision-based robotic bin-picking system for robotic assembly tasks, which was awarded the 100 most innovative technology products of the year by the R&D magazine in 2014. He is a recipient of a paper award from the robotics science and system (RSS) 2015 conference for his street scene understanding work. Recently, his research focus shifted to deep generative models for image understanding and generation. His goal is to enable machines superhuman-like imagination capabilities.

Check out my new code release in GitHub. Follow me on Twitter Twitter


Publication

    2011


Patents granted

  • US 9,633,274: Method and system for denoising images using deep Gaussian conditional random field network

  • US 9,558,268: Method for semantically labeling an image of a scene using recursive context propagation

  • US 8,428,363: Method for segmenting images using superpixels and entropy rate clustering

  • US 8,983,177: Method for increasing resolutions of depth images

  • US 8,908,913: Voting-based pose estimation for 3D sensors

  • US 9,195,904: Method for detecting objects in stereo images

  • US 9,280,827: Method for determining object poses using Weighted Features

  • My MERL patents


Education

  • PhD, Electrical&Computer Engineering, University of Maryland College Park, Advisor: Rama Chellappa, 2006-2012


Tutorial

  • CVPR2017: Theory and Applications of Generative Adversarial Networks, [Site]

  • ACCV2016: Deep Learning for Vision Guided Language Generation and Image Generation, [Site]


Awards


Research


Service

  • Reviewers: NIPS, CVPR, ECCV, ICCV

  • Area Chairs: WACV

  • NSF proposal reviewer