Yonglong Tian


Ph.D. Student
EECS, MIT, Cambridge MA
Email: yonglong@mit.edu


Google Scholar GitHub

About Me

Hi, welcome to my website!

I am a third-year Ph.D. student at MIT CSAIL, working with Prof. Phillip Isola and Prof. Josh Tenenbaum. My main research interests lie in the intersection of machine perception, learning and reasoning, mainly from the perspective of vision.

Prior to MIT, I completed my M.Phil degree at CUHK, advised by Prof. Xiaoou Tang and Prof. Xiaogang Wang. I did my undergraduate study at Tsinghua University.

Updates


June, 2020: Gave a talk about Contrastive Learning at MIT Vision Seminar, find the Video Recording.

May, 2020: A PyTorch library of unsupervised contrastive learning approaches is released, see Github.

April, 2020: PyTorch code for SupContrast and SimCLR, see Repo.

Publications

Preprints

Training-Free Uncertainty Estimation for Neural Networks

Lu Mi, Hao Wang, Yonglong Tian, Nir Shavit
arXiv:1910.04858
arXiv



2020

What Makes for Good Views for Contrastive Learning?

Yonglong Tian, Chen Sun, Ben Poole, Dilip Krishnan, Cordelia Schmid, Phillip Isola
Advances In Neural Information Processing Systems (NeurIPS), 2020
arXiv Project Page Code




Supervised Contrastive Learning

Prannay Khosla, Piotr Teterwak, Chen Wang, Aaron Sarna, Yonglong Tian, Phillip Isola, Aaron Maschinot, Ce Liu, Dilip Krishnan
Advances In Neural Information Processing Systems (NeurIPS), 2020
Paper PyTorch



Rethinking Few-Shot Image Classification: a Good Embedding Is All You Need?

Yonglong Tian*, Yue Wang*, Dilip Krishnan, Joshua B. Tenenbaum, Phillip Isola
European Conference on Computer Vision (ECCV), 2020
Paper Project Page Code




Contrastive Multiview Coding

Yonglong Tian, Dilip Krishnan, Phillip Isola
arXiv:1906.05849
European Conference on Computer Vision (ECCV), 2020
Paper Project Page Code



Contrastive Representation Distillation

Yonglong Tian, Dilip Krishnan, Phillip Isola
arXiv:1910.10699
International Conference on Learning Representations (ICLR), 2020
Paper arXiv Project Page Code



2019

Contrastive Multiview Coding

Yonglong Tian, Dilip Krishnan, Phillip Isola
arXiv:1906.05849
Workshop on Self-supervised Learning (ICML workshop), 2019
arXiv Project Page Short version Code



Learning to Infer and Execute 3D Shape Programs

Yonglong Tian, Andrew Luo, Xingyuan Sun, Kevin Ellis, William T. Freeman, Joshua B. Tenenbaum, Jiajun Wu
International Conference on Learning Representations (ICLR), 2019
Paper Project Page Poster Code



ProbGAN: Towards Probabilistic GAN with Theoretical Guarantees

Hao He, Hao Wang, Guang-He Lee, Yonglong Tian.
International Conference on Learning Representations (ICLR), 2019
Paper Code



2018

RF-Based Fall Monitoring Using Convolutional Neural Networks

Yonglong Tian*, Guang-He Lee*, Hao He*, Chen-Yu Hsu, Dina Katabi.
ACM International Joint Conference on Pervasive and Ubiquitous Computing (Ubicomp/IMWUT), 2018
Paper Slides Project Page



RF-Based 3D Skeletons

Mingmin Zhao, Yonglong Tian, Hang Zhao, Mohammad Abu Alsheikh, Tianhong Li, Rumen Hristov, Zachary Kabelac, Dina Katabi, Antonio Torralba.
Special Interest Group on Data Communications (SIGCOMM), 2018
Paper Project Page Video



Bayesian Modelling and Monte Carlo Inference for GAN

Hao He, Hao Wang, Guang-He Lee, Yonglong Tian.
Theoretical Foundations and Applications of Deep Generative Models (ICML workshop), 2018
Paper



Representation Learning on Graphs with Jumping Knowledge Networks

Keyulu Xu, Chengtao Li, Yonglong Tian, Tomohiro Sonobe, Ken-ichi Kawarabayashi, Stefanie Jegelka.
International Conference on Machine Learning (ICML), 2018
Paper Supplementary




Through-Wall Human Pose Estimation Using Radio Signals

Mingmin Zhao, Tianhong Li, Mohammad Alsheikh, Yonglong Tian, Hang Zhao, Dina Katabi, Antonio Torralba.
Computer Vision and Pattern Recognition (CVPR), 2018
Paper Project Page Poster Video MIT News




Before Ph.D.

DeepID-Net: Object Detection with Deformable Part Based Convolutional Neural Networks

Wanli Ouyang, Xingyu Zeng, Xiaogang Wang, Shi Qiu, Ping Luo, Yonglong Tian, et. al.
Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2017
Paper Project Page




Deep Learning Strong Parts for Pedestrian Detection

Yonglong Tian, Ping Luo, Xiaogang Wang, Xiaoou Tang.
International Conference on Computer Vision (ICCV), 2015
Paper Poster



Pedestrian Detection aided by Deep Learning Semantic Tasks

Yonglong Tian, Ping Luo, Xiaogang Wang, Xiaoou Tang.
Computer Vision and Pattern Recognition (CVPR), 2015
Paper Poster Project Page



DeepID-Net: Deformable Deep Convolutional Neural Networks for Object Detection

Wanli Ouyang, Xiaogang Wang, Xingyu Zeng, Shi Qiu, Ping Luo, Yonglong Tian, et. al.
Computer Vision and Pattern Recognition (CVPR), 2015
Paper arXiv Project Page




Switchable Deep Network for Pedestrian Detection

Yonglong Tian*, Ping Luo*, Xiaogang Wang, Xiaoou Tang.
Computer Vision and Pattern Recognition (CVPR), 2014
Paper Video Supplementary

Teaching


MIT:

6.869: Advances in Computer Vision, 2018 Fall

CUHK:

ENGG2430: Probability and Statistics

IERG3921: Information Engineering and Practice

IERG3060: Microcontrollers and Embedded Systems

Services


Conference Reviwer: ECCV'16, ECCV'18, CVPR'17, CVPR'18, CVPR'19, ICCV'17, ICCV'19, NIPS'19

Journal Reviwer: T-MM, T-CVST
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