Ming-Yu Liu is a principal research scientist at NVIDIA Research. Before joining NVIDIA in 2016, he was a principal research scientist 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 object pose estimation system was awarded one of hundred most innovative technology products by the R&D magazine in 2014. His street scene understanding paper was selected in the best paper finalist in the 2015 Robotics Science and System (RSS) conference. In CVPR 2018, he won the 1st place in both the Domain Adaptation for Semantic Segmentation Competition in the WAD challenge and the Optical Flow Competition in the Robust Vision Challenge. His research focus is on generative models for image generation and understanding. His goal is to enable machines superhuman-like imagination capabilities.

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Research focus

SPADE Semantic Image Synthesis with Spatially-Adaptive Normalization (CVPR 2019)

vid2vid Video-to-Video Synthesis (NeurIPS 2018, arxiv 2018)

MUNIT Multimodal unsupervised image-to-image translation (ECCV 2018)

FastPhotoStyle Transfer style of a real photo to another real photo (ECCV 2018)

pix2pixHD High-res image synthesis and semantic manipulation (CVPR 2018)

CoupledGAN Unsupervised image-to-image translation (NeurIPS 2016, NeurIPS 2017)
Left: input; right: machine-generated

MoCoGAN for video generation (CVPR 2018)

Former research focus


Academic Service

  • Conference reviewer: CVPR, ICCV, ECCV, NIPS, ICML, ICLR

  • Journal reviewer: TPAMI, IJCV, TIP, TMM, CVIU

  • Journal guess editor: IJCV, CVIU

  • Area chair: ICCV, BMVC, WACV


  • CVPR 2019 Tutorial: Deep Learning for Content Creation

  • ICIP 2019 Tutorial: Image-to-Image Translation

  • CVPR 2017 Tutorial: Theory and Applications of Generative Adversarial Networks, [Site]

  • ACCV 2016 Tutorial: Deep Learning for Vision Guided Language Generation and Image Generation, [Site]


  • CVPR 2019 Workshop: 4th New Trends in Image Restoration and Enhancement workshop and challenges

  • CVPR 2019 Workshop: AI City Challenge, [Site]

  • CVPR 2018 Workshop: AI City Challenge, [Site]