Seuraa
Yonglong Tian
Yonglong Tian
Google Research; MIT
Vahvistettu sähköpostiosoite verkkotunnuksessa mit.edu - Kotisivu
Nimike
Viittaukset
Viittaukset
Vuosi
Supervised contrastive learning
P Khosla, P Teterwak, C Wang, A Sarna, Y Tian, P Isola, A Maschinot, ...
NeurIPS 2020, 2020
28042020
Contrastive multiview coding
Y Tian, D Krishnan, P Isola
arXiv preprint arXiv:1906.05849, 2019
19482019
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
16412018
What makes for good views for contrastive learning
Y Tian, C Sun, B Poole, D Krishnan, C Schmid, P Isola
NeurIPS 2020, 2020
9392020
Contrastive representation distillation
Y Tian, D Krishnan, P Isola
International Conference on Learning Representations (ICLR), 2020
8162020
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
7372020
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
5872015
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
5442015
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
5312018
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
4962015
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
3102014
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
2952018
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
1712014
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
1502017
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
1372018
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
1352019
Generative models as a data source for multiview representation learning
A Jahanian, X Puig, Y Tian, P Isola
arXiv preprint arXiv:2106.05258, 2021
582021
Divide and Contrast: Self-supervised Learning from Uncurated Data
Y Tian, OJ Henaff, A Oord
International Conference on Computer Vision (ICCV), 2021
582021
ProbGAN: Towards Probabilistic GAN with Theoretical Guarantees
H He, H Wang, GH Lee, Y Tian
International Conference on Learning Representations (ICLR), 2019
342019
Training-free uncertainty estimation for neural networks
L Mi, H Wang, Y Tian, N Shavit
33*2019
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Artikkelit 1–20