Yonglong Tian
Yonglong Tian
Ph.D. student, MIT
Verified email at mit.edu - Homepage
Title
Cited by
Cited by
Year
Deep Learning Strong Parts for Pedestrian Detection
Y Tian, P Luo, X Wang, X Tang
Computer Vision (ICCV), 2015 IEEE International Conference on, 1904-1912, 2015
3762015
Pedestrian detection aided by deep learning semantic tasks
Y Tian, P Luo, X Wang, X Tang
Computer Vision and Pattern Recognition (CVPR), 2015 IEEE Conference on, 2015
3692015
Deepid-net: Deformable deep convolutional neural networks for object detection
W Ouyang, X Wang, X Zeng, S Qiu, P Luo, Y Tian, H Li, S Yang, Z Wang, ...
Proceedings of the IEEE conference on computer vision and pattern …, 2015
3522015
Representation Learning on Graphs with Jumping Knowledge Networks
K Xu, C Li, Y Tian, T Sonobe, K Kawarabayashi, S Jegelka
International Conference on Machine Learning (ICML), 2018
2982018
Switchable deep network for pedestrian detection
Y Tian*, P Luo*, X Wang, X Tang
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2014
2512014
Contrastive multiview coding
Y Tian, D Krishnan, P Isola
European Conference on Computer Vision (ECCV 2020), 2020
2172020
Through-wall human pose estimation using radio signals
M Zhao, T Li, M Abu Alsheikh, Y Tian, H Zhao, A Torralba, D Katabi
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
1692018
Deepid-net: multi-stage and deformable deep convolutional neural networks for object detection
W Ouyang, P Luo, X Zeng, S Qiu, Y Tian, H Li, S Yang, Z Wang, Y Xiong, ...
arXiv preprint arXiv:1409.3505, 2014
1252014
RF-based 3D skeletons
M Zhao, Y Tian, H Zhao, MA Alsheikh, T Li, R Hristov, Z Kabelac, D Katabi, ...
ACM SIGCOMM 2018, 267-281, 2018
752018
Contrastive representation distillation
Y Tian, D Krishnan, P Isola
International Conference on Learning Representations (ICLR), 2020
622020
DeepID-Net: Object Detection with Deformable Part Based Convolutional Neural Networks
W Ouyang, X Zeng, X Wang, S Qiu, P Luo, Y Tian, H Li, S Yang, Z Wang, ...
IEEE Transactions on Pattern Analysis and Machine Intelligence 39 (7), 1320-1334, 2017
602017
Learning to Infer and Execute 3D Shape Programs
Y Tian, A Luo, X Sun, K Ellis, WT Freeman, JB Tenenbaum, J Wu
International Conference on Learning Representations (ICLR), 2019
452019
RF-based fall monitoring using convolutional neural networks
Y Tian, GH Lee, H He, CY Hsu, D Katabi
ACM UbiComp 2018 2 (3), 1-24, 2018
382018
What makes for good views for contrastive learning
Y Tian, C Sun, B Poole, D Krishnan, C Schmid, P Isola
NeurIPS 2020, 2020
372020
Supervised contrastive learning
P Khosla, P Teterwak, C Wang, A Sarna, Y Tian, P Isola, A Maschinot, ...
NeurIPS 2020, 2020
362020
Rethinking Few-Shot Image Classification: a Good Embedding Is All You Need?
Y Tian, Y Wang, D Krishnan, JB Tenenbaum, P Isola
European Conference on Computer Vision (ECCV 2020), 2020
232020
ProbGAN: Towards Probabilistic GAN with Theoretical Guarantees
H He, H Wang, GH Lee, Y Tian
International Conference on Learning Representations (ICLR), 2019
82019
Bayesian Modelling and Monte Carlo Inference for GAN
H He, H Wang, GH Lee, Y Tian
The ICML 2018 workshop on Theoretical Foundations and Applications of Deep …, 2018
42018
Pose estimation
D Katabi, A Torralba, H Zhao, M Zhao, M Abualsheikh, Y Tian
US Patent App. 16/225,837, 2019
32019
Training-free uncertainty estimation for neural networks
L Mi, H Wang, Y Tian, N Shavit
arXiv preprint arXiv:1910.04858, 2019
22019
The system can't perform the operation now. Try again later.
Articles 1–20