Papers,
Patents,
Papers
Awarded Patents
My NVIDIA patents.
US 11,082,720: Using residual video data resulting from a compression of original video data to improve a decompression of the original video data
US 11,017,556: Iterative spatio-temporal action detection in video
US 10,984,286: Domain stylization using a neural network model
US 10,922,792: Guided hallucination for missing image content using a neural network
US 10,872,399: Photorealistic image stylization using a neural network model
US 10,789,678: Superpixel sampling networks
US 10,748,036: Training a neural network to predict superpixels using segmentation-aware affinity loss
US 10,595,039: System and method for content and motion controlled action video generation
US 10,593,020: Unsupervised learning approach for video deblurring
US 10,424,069: System and method for optical flow estimation
My MERL patents.
US 9,989,964: System and Method for Controlling Vehicle Using Neural Network
US 9,971,958: Method and System for Generating Multimodal Digital Images
US 9,811,756: Method for Labeling Images of Street Scenes
US 9,805,294: Method for Denoising Time-of-Flight Range Images
US 9,704,257: System and method for semantic segmentation using Gaussian random field network
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 9,280,827: Method for determining object poses using Weighted Features
US 9,195,904: Method for detecting objects in stereo images
US 8,983,177: Method for increasing resolutions of depth images
US 8,908,913: Voting-based pose estimation for 3D sensors
US 8,428,363: Method for segmenting images using superpixels and entropy rate clustering
Papers
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Multimodal Conditional Image Synthesis with Product-of-Experts GANs Xun Huang, Arun Mallya, Ting-Chun Wang, Ming-Yu Liu arXiv:2112.05130 [Project] |
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Deep Marching Tetrahedra: a Hybrid Representation for High-Resolution 3D Shape Synthesis Tianchang Shen, Jun Gao, Kangxue Yin, Ming-Yu Liu, Sanja Fidler NeurIPS 2021 |
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I am AI: AI-driven Digital Avatar Made Easy Ming-Yu Liu, Koki Nagano, Yeongho Seol, Rafael Valle, Jaewoo Seo, Ting-Chun Wang, Arun Mallya, Sameh Khamis, Wei Ping, Rohan Badlani, Kevin J. Shih, Bryan Catanzaro, Simon Yuen, Jan Kautz SIGGRAPH RTL 2021 (Best-in-Show) |
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GANcraft: Unsupervised 3D Neural Rendering of Minecraft Worlds Zekun Hao, Arun Mallya, Serge Belongie, Ming-Yu Liu ICCV 2021 (Oral) [Project] [Demo] [Video] |
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One-Shot Free-View Neural Talking-Head Synthesis for Video Conferencing Ting-Chun Wang, Arun Mallya, Ming-Yu Liu CVPR 2021 (Oral) [Project] [Video] |
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Generative Adversarial Networks for Image and Video Synthesis: Algorithms and Applications Ming-Yu Liu, Xun Huang, Jiahui Yu, Ting-Chun Wang, Arun Mallya Proceedings of the IEEE, 2021 |
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Learning compositional functions via multiplicative weight updates Jeremy Bernstein, Jiawei Zhao, Markus Meister, Ming-Yu Liu, Anima Anandkumar, Yisong Yue NeurIPS 2020 [Code] |
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On the distance between two neural networks and the stability of learning Jeremy Bernstein, Arash Vahdat, Yisong Yue, Ming-Yu Liu NeurIPS 2020 [Blog] [Code] |
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COCO-FUNIT: Few-Shot Unsupervised Image Translation with a Content Conditioned Style Encoder Kuniaki Saito, Kate Saenko, Ming-Yu Liu ECCV 2020 (Spotlight) [Project] [Code] [Video] |
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World-Consistent Video-to-Video Synthesis Arun Mallya, Ting-Chun Wang, Karan Sapra, Ming-Yu Liu ECCV 2020 [Project] [Code] [Video] |
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UFO2: A Unified Framework Towards Omni-supervised Object Detection Zhongzheng Ren, Zhiding Yu, Xiaodong Yang, Ming-Yu Liu, Alex Schwing, Jan Kautz ECCV 2020 [Project] [Code] [Video] |
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UNAS: Differentiable Architecture Search Meets Reinforcement Learning Arash Vahdat, Arun Mallya, Ming-Yu Liu, Jan Kautz CVPR 2020 [Code] |
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Instance-aware, Context-focused, and Memory-efficient Weakly-Supervised Object Detection Zhongzheng Ren, Zhiding Yu, Xiaodong Yang, Ming-Yu Liu, Yong Jae Lee, Alexander Schwing, Jan Kautz CVPR 2020 [Code] |
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Learning to Generate Multiple Style Transfer Outputs for an Input Sentence Kevin Lin, Ming-Yu Liu, Ming-Ting Sun, Jan Kautz ACL 2020 (Workshop) |
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Style Example-Guided Text Generation using Generative Adversarial Transformers Kuo-Hao Zeng, Mohammad Shoeybi, Ming-Yu Liu arXiv:2003.00674 |
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Domain Stylization: A Fast Covariance Matching Framework towards Domain Adaptation Aysegul Dundar, Ming-Yu Liu, Zhiding Yu, Ting-Chun Wang, John Zedlewski, Jan Kautz TPAMI 2020 |
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SymGAN: Orientation Estimation without Annotation for Symmetric Objects Phil Ammirato, Jonathan Tremblay, Ming-Yu Liu, Alexander Berg, Dieter Fox WACV 2020 |
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Few-Shot Video-to-Video Synthesis Ting-Chun Wang, Ming-Yu Liu, Andrew Tao, Guilin Liu, Jan Kautz, Bryan Catanzaro NeurIPS 2019 [Project] [Code] [Video] |
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Dancing to Music Hsin-Ying Lee, Xiaodong Yang, Ming-Yu Liu, Ting-Chun Wang, Yu-Ding Lu, Ming-Hsuan Yang, Jan Kautz NeurIPS 2019 [Code] |
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Few-Shot Unsupervised Image-to-Image Translation Ming-Yu Liu, Xun Huang, Arun Mallya, Tero Karras, Timo Aila, Jaakko Lehtinen, Jan Kautz ICCV 2019 [Project] [Demo] [Code] |
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PointFlow: 3D Point Cloud Generation with Continuous Normalizing Flows Guandao Yang, Xun Huang, Zekun Hao, Ming-Yu Liu, Serge Belongie, Bharath Hariharan ICCV 2019 (Oral) [Project] [Code] |
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Neural Turtle Graphics for Modeling City Road Layouts Hang Chu, Daiqing Li, David Acuna, Amlan Kar, Maria Shugrina, Xinkai Wei, Ming-Yu Liu, Antonio Torralba, Sanja Fidler ICCV 2019 (Oral) [Code] |
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Meta-Sim: Learning to Generate Synthetic Datasets Amlan Kar, Aayush Prakash, Ming-Yu Liu, Eric Cameracci, Justin Yuan, Matt Rusiniak, David Acuna, Antonio Torralba, Sanja Fidler ICCV 2019 (Oral) [Code] |
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Boosting segmentation with weak supervision from image-to-image translation Eugene Vorontsov, Pavlo Molchanov, Wonmin Byeon, Shalini De Mello, Varun Jampani, Ming-Yu Liu, Samuel Kadoury, Jan Kautz arxiv:1904.01636 |
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GauGAN: Semantic Image Synthesis With Spatially Adaptive Normalization Taesung Park, Chris Hebert, Ting-Chun Wang, Jun-Yan Zhu, Gavriil Klimov, Ming-Yu Liu SIGGRAPH Real-Time-Live 2019 (Best-in-Show, Audience Choice) |
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Semantic Image Synthesis with Spatially-Adaptive Normalization Taesung Park, Ming-Yu Liu, Ting-Chun Wang, Jun-Yan Zhu CVPR 2019 (Oral, Best Paper Finalist) [Project] [Demo] [Code] [Video] |
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CityFlow: A City-Scale Benchmark for Multi-Target Multi-Camera Vehicle Tracking and Re-Identification Zheng Tang, Milind Naphade, Ming-Yu Liu, Xiaodong Yang, Stan Birchfield, Shuo Wang, Ratnesh Kumar, David Anastasiu, Jenq-Neng Hwang CVPR 2019 (Oral) |
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STEP: Spatio-TempOral, Progressive Learning for Video Action Detection Xitong Yang, Xiaodong Yang, Ming-Yu Liu, Fanyi Xiao, Larry Davis, Jan Kautz CVPR 2019 (Oral) [Code] |
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Models Matter, So Does Training: An Empirical Study of CNNs for Optical Flow Estimation Deqing Sun, Xiaodong Yang, Ming-Yu Liu, Jan Kautz TPAMI 2019 |
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Unsupervised Stylish Image Description Generation via Domain Layer Norm Cheng-Kuan Chen, Zhu-Feng Pan, Ming-Yu Liu, Min Sun AAAI 2019 |
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Video-to-Video Synthesis Ting-Chun Wang, Ming-Yu Liu, Jun-Yan Zhu, Guilin Liu, Andrew Tao, Jan Kautz, Bryan Catanzaro NeurIPS 2018 [Project] [Code] [Video] |
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Context-aware Synthesis and Placement of Object Instances Donghoon Lee, Sifei Liu, Jinwei Gu, Ming-Yu Liu, Ming-Hsuan Yang, Jan Kautz NeurIPS 2018 [Code] |
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Localization-Aware Active Learning for Object Detection Chieh-Chi Kao, Teng-Yok Lee, Pradeep Sen, Ming-Yu Liu ACCV 2019 |
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Domain Stylization: A Strong, Simple Baseline for Synthetic to Real Image Domain Adaptation Aysegul Dundar, Ming-Yu Liu, Ting-Chun Wang, John Zedlewski, Jan Kautz arXiv:1807.09384 |
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Multimodal Unsupervised Image-to-Image Translation Xun Huang, Ming-Yu Liu, Serge Belongie, Jan Kautz ECCV 2018 [Code] [Video] |
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A Closed-form Solution to Photorealistic Image Stylization Yijun Li, Ming-Yu Liu, Xueting Li, Ming-Hsuan Yang, Jan Kautz ECCV 2018 [Code] [Video] |
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Superpixel Sampling Networks Varun Jampani, Deqing Sun, Ming-Yu Liu, Ming-Hsuan Yang, Jan Kautz ECCV 2018 [Code] |
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Reblur2Deblur: Deblurring Videos via Self-Supervised Learning Huaijin Chen, Jinwei Gu, Orazio Gallo, Ming-Yu Liu, Ashok Veeraraghavan, Jan Kautz ICCP 2018 |
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PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume Deqing Sun, Xiaodong Yang, Ming-Yu Liu, Jan Kautz CVPR 2018 (Oral) [Code] |
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Learning Superpixels with Segmentation-Aware Affinity Loss Wei-Chih Tu, Ming-Yu Liu, Varun Jampani, Deqing Sun, Shao-Yi Chien, Ming-Hsuan Yang, Jan Kautz CVPR 2018 [Code] |
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MoCoGAN: Decomposing Motion and Content for Video Generation Sergey Tulyakov, Ming-Yu Liu, Xiaodong Yang, Jan Kautz CVPR 2018 [Code] |
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The 2018 NVIDIA AI City Challenge Milind Naphade, Ming-Ching Chang, Anuj Sharma, David C. Anastasiu, Vamsi Jagarlamudi, Pranamesh Chakraborty, Tingting Huang, Shuo Wang, Ming-Yu Liu, Rama Chellappa, Jenq-Neng Hwang, and Siwei Lyu CVPR 2018 (Workshop) |
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Learning Binary Residual Representations for Domain-specific Video Streaming Yi-Hsuan Tsai, Ming-Yu Liu, Deqing Sun, Ming-Hsuan Yang, Jan Kautz AAAI 2018 |
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Unsupervised Image-to-Image Translation Networks Ming-Yu Liu, Thomas Breuel, Jan Kautz NeurIPS 2017 [Code] |
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Detecting Adversarial Attacks on Neural Network Policies with Visual Foresight Yen-Chen Lin, Ming-Yu Liu, Min Sun, Jia-Bin Huang NeurIPS 2017 (Workshop) [Code] |
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Tactics of Adversarial Attack on Deep Reinforcement Learning Agents Yen-Chen Lin, Zhang-Wei Hong, Yuan-Hong Liao, Meng-Li Shih, Ming-Yu Liu, Min Sun IJCAI 2017 [Project] |
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Deep 360 Pilot: Learning a Deep Agent for Piloting through 360 Sports Videos Hou-Ning Hu*, Yen-Chen Lin*, Ming-Yu Liu, Hsien-Tzu Cheng, Stanley Chang, Min Sun CVPR 2017 (Oral) |
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CASENet: Deep Category-Aware Semantic Edge Detection Zhiding Yu, Chen Feng, Ming-Yu Liu, Srikumar Ramalingam CVPR 2017 [Code] |
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Deep Active Learning for Civil Infrastructure Defect Detection and Classification Chen Feng, Ming-Yu Liu, Chieh-Chi Kao, Teng-Yok Lee IWCCE 2017 |
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Attentional Network for Visual Object Detection Kota Hara, Ming-Yu Liu, Oncel Tuzel, Amir-massoud Farahmand arXiv:1702.01478 |
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Coupled Generative Adversarial Networks Ming-Yu Liu, Oncel Tuzel NeurIPS 2016 [Code] |
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R-CNN for Small Object Detection Chenyi Chen, Ming-Yu Liu, Oncel Tuzel, Jianxiong Xiao ACCV 2016 |
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Gaussian Conditional Random Field Network for Semantic Segmentation Raviteja Vemulapalli, Oncel Tuzel, Ming-Yu Liu, Rama Chellappa CVPR 2016 (Spotlight) |
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Deep Gaussian Conditional Random Field Network: A Model-based Deep Network for Discriminative Denoising Raviteja Vemulapalli, Oncel Tuzel, Ming-Yu Liu CVPR 2016 |
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Learning to Remove Multipath Distortions in Time-of-Flight Range Images for a Robotic Arm Setup ICRA 2016 [Dataset] |
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Unsupervised Network Pretraining via Encoding Human Design Ming-Yu Liu, Arun Mallya, Oncel Tuzel, Xi Chen WACV 2016 |
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Layered Interpretation of Street View Images Ming-Yu Liu, Shuoxin Lin, Srikumar Ramalingam, Oncel Tuzel RSS 2015 (Best Paper Finalist) |
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Recursive Context Propagation Network for Semantic Scene Labeling Abhishek Sharma, Oncel Tuzel, Ming-Yu Liu NeurIPS 2014 |
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Learning to Rankd 3D Features Oncel Tuzel, Ming-Yu Liu, Yuichi Taguchi, Arvind Raghunathan ECCV 2014 |
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Joint Geodesic Upsampling of Depth Images Ming-Yu Liu, Oncel Tuzel, Yuichi Taguchi CVPR 2013 [Results] [Code] |
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Entropy Rate Clustering: Cluster Analysis via Maximizing a Submodular Function Subject to a Matroid Constraint Ming-Yu Liu, Oncel Tuzel, Srikumar Ramalingam, Rama Chellappa TPAMI 2013 |
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Model-based Vehicle Pose Estimation and Tracking in Videos Using Random Forests Michael Hodlmoser, Branislav Micusik, Marc Pollefeys, Ming-Yu Liu, Martin Kampel 3DV 2013 |
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Fast Object Localization and Pose Estimation in Heavy Clutter for Robotic Bin Picking Ming-Yu Liu, Oncel Tuzel, Ashok Veeraraghavan, Yuichi Taguchi, Tim K. Marks, Rama Chellappa IJRR 2012 [Code] |
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A Grassmann Manifold-based Domain Adaptation Approach Jingjing Zheng, Ming-Yu Liu, Rama Chellappa, P Jonathan Phillips ICPR 2012 (Oral) |
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Classification and Pose Estimation of Vehicles in Videos by 3D Modeling within Discrete-Continuous Optimization Michael Hödlmoser, Branislav Micusik, Ming-Yu Liu, Marc Pollefeys, Martin Kampel 3DV 2012 |
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Entropy Rate Superpixel Segmentation Ming-Yu Liu, Oncel Tuzel, Srikumar Ramalingam, Rama Chellappa CVPR 2011 [Code] |
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Fast Directional Chamfer Matching Ming-Yu Liu, Oncel Tuzel, Srikumar Ramalingam, Rama Chellappa CVPR 2010 [Code] |
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Pose Estimation in Heavy Clutter Using a Multi-Flash Camera Ming-Yu Liu, Oncel Tuzel, Ashok Veeraraghavan, Rama Chellappa, Amit Agrawal, Haruhisa Okuda ICRA 2010 |
Awarded Patents
US 11,082,720: Using residual video data resulting from a compression of original video data to improve a decompression of the original video data
US 11,017,556: Iterative spatio-temporal action detection in video
US 10,984,286: Domain stylization using a neural network model
US 10,922,792: Guided hallucination for missing image content using a neural network
US 10,872,399: Photorealistic image stylization using a neural network model
US 10,789,678: Superpixel sampling networks
US 10,748,036: Training a neural network to predict superpixels using segmentation-aware affinity loss
US 10,595,039: System and method for content and motion controlled action video generation
US 10,593,020: Unsupervised learning approach for video deblurring
US 10,424,069: System and method for optical flow estimation
US 9,989,964: System and Method for Controlling Vehicle Using Neural Network
US 9,971,958: Method and System for Generating Multimodal Digital Images
US 9,811,756: Method for Labeling Images of Street Scenes
US 9,805,294: Method for Denoising Time-of-Flight Range Images
US 9,704,257: System and method for semantic segmentation using Gaussian random field network
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 9,280,827: Method for determining object poses using Weighted Features
US 9,195,904: Method for detecting objects in stereo images
US 8,983,177: Method for increasing resolutions of depth images
US 8,908,913: Voting-based pose estimation for 3D sensors
US 8,428,363: Method for segmenting images using superpixels and entropy rate clustering