Xiaohua Zhai
Xiaohua Zhai
Google Brain
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An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
A Dosovitskiy*, L Beyer*, A Kolesnikov*, D Weissenborn*, X Zhai*, ...
International Conference on Learning Representations (ICLR), 2021
Big Transfer (BiT): General Visual Representation Learning
A Kolesnikov*, L Beyer*, X Zhai*, J Puigcerver, J Yung, S Gelly, ...
European Conference on Computer Vision (ECCV), 2020
Revisiting Self-Supervised Visual Representation Learning
A Kolesnikov*, X Zhai*, L Beyer*, *equal contribution
Computer Vision and Pattern Recognition (CVPR), 2019
S4l: Self-supervised semi-supervised learning
X Zhai*, A Oliver*, A Kolesnikov*, L Beyer*, *equal contribution
International Conference on Computer Vision (ICCV), 1476-1485, 2019
MLP-Mixer: An all-MLP Architecture for Vision
I Tolstikhin*, N Houlsby*, A Kolesnikov*, L Beyer*, X Zhai, T Unterthiner, ...
Advances in Neural Information Processing Systems (NeurIPS), 2021
Underspecification Presents Challenges for Credibility in Modern Machine Learning
A D'Amour*, K Heller*, D Moldovan*, B Adlam, B Alipanahi, A Beutel, ...
Journal of Machine Learning Research (JMLR), 2020
Learning cross-media joint representation with sparse and semisupervised regularization
X Zhai, Y Peng, J Xiao
IEEE Transactions on Circuits and Systems for Video Technology 24 (6), 965-978, 2013
Self-Supervised GANs via Auxiliary Rotation Loss
T Chen, X Zhai, M Ritter, M Lucic, N Houlsby
Computer Vision and Pattern Recognition (CVPR), 12154-12163, 2019
An image is worth 16x16 words: Transformers for image recognition at scale. arXiv 2020
A Dosovitskiy, L Beyer, A Kolesnikov, D Weissenborn, X Zhai, ...
arXiv preprint arXiv:2010.11929, 2010
A large-scale study on regularization and normalization in GANs
K Kurach, M Lučić, X Zhai, M Michalski, S Gelly
International Conference on Machine Learning, 3581-3590, 2019
The gan landscape: Losses, architectures, regularization, and normalization
K Kurach, M Lucic, X Zhai, M Michalski, S Gelly
International Conference on Machine Learning (ICML), 2019
Heterogeneous metric learning with joint graph regularization for cross-media retrieval
X Zhai, Y Peng, J Xiao
Twenty-seventh AAAI conference on artificial intelligence, 2013
Semi-supervised cross-media feature learning with unified patch graph regularization
Y Peng, X Zhai, Y Zhao, X Huang
IEEE transactions on circuits and systems for video technology 26 (3), 583-596, 2015
High-Fidelity Image Generation With Fewer Labels
M Lučić, M Tschannen, M Ritter, X Zhai, O Bachem, S Gelly
International Conference on Machine Learning (ICML), 4183-4192, 2019
A Large-scale Study of Representation Learning with the Visual Task Adaptation Benchmark
X Zhai*, J Puigcerver*, A Kolesnikov*, P Ruyssen, C Riquelme, M Lucic, ...
arXiv preprint arXiv:1910.04867, 2019
Are we done with ImageNet?
L Beyer*, OJ Hénaff*, A Kolesnikov*, X Zhai*, A Oord*, *equal contribution
arXiv preprint arXiv:2006.07159, 2020
How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers
A Steiner*, A Kolesnikov*, X Zhai*, R Wightman, J Uszkoreit, L Beyer*, ...
arXiv preprint arXiv:2106.10270, 2021
Cross-modality correlation propagation for cross-media retrieval
X Zhai, Y Peng, J Xiao
International Conference on Acoustics, Speech and Signal Processing (ICASSP …, 2012
On Robustness and Transferability of Convolutional Neural Networks
J Djolonga*, J Yung*, M Tschannen*, R Romijnders, L Beyer, ...
Computer Vision and Pattern Recognition (CVPR), 2021
Self-Supervised Learning of Video-Induced Visual Invariances
M Tschannen, J Djolonga, M Ritter, A Mahendran, X Zhai, N Houlsby, ...
arXiv preprint: 1912.02783, 2020
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