| 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), 2020 | 49546 | 2020 |
| iCaRL: Incremental Classifier and Representation Learning SA Rebuffi, A Kolesnikov, G Sperl, CH Lampert IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2017 | 4349 | 2017 |
| The open images dataset v4: Unified image classification, object detection, and visual relationship detection at scale A Kuznetsova, H Rom, N Alldrin, J Uijlings, I Krasin, J Pont-Tuset, ... International Journal of Computer Vision (2018), 2018 | 2887 | 2018 |
| MLP-Mixer: An all-MLP Architecture for Vision I Tolstikhin*, N Houlsby*, A Kolesnikov*, L Beyer*, X Zhai, T Unterthiner, ... Neural Information Processing Systems (NeurIPS), 2021 | 2842 | 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 | 1453 | 2020 |
| Scaling Vision Transformers X Zhai*, A Kolesnikov*, N Houlsby, L Beyer*, *equal contribution IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 | 1198 | 2022 |
| S4L: Self-Supervised Semi-Supervised Learning X Zhai*, A Oliver*, A Kolesnikov*, L Beyer*, *equal contribution IEEE/CVF International Conference on Computer Vision (ICCV), 2019 | 1063 | 2019 |
| Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation A Kolesnikov, CH Lampert European Conference on Computer Vision (ECCV), 2016 | 905 | 2016 |
| Revisiting Self-Supervised Visual Representation Learning A Kolesnikov*, X Zhai*, L Beyer*, *equal contribtion IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019 | 892 | 2019 |
| How to train your vit? data, augmentation, and regularization in vision transformers A Steiner, A Kolesnikov, X Zhai, R Wightman, J Uszkoreit, L Beyer Transactions on Machine Learning Research (TMLR), 2021 | 670 | 2021 |
| Pali: A jointly-scaled multilingual language-image model X Chen, X Wang, S Changpinyo, AJ Piergiovanni, P Padlewski, D Salz, ... International Conference on Learning Representations (ICLR), 2022 | 614 | 2022 |
| LiT: Zero-Shot Transfer with Locked-image Text Tuning X Zhai, X Wang, B Mustafa, A Steiner, D Keysers, A Kolesnikov, L Beyer IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 | 541 | 2021 |
| Scaling vision transformers to 22 billion parameters M Dehghani, J Djolonga, B Mustafa, P Padlewski, J Heek, J Gilmer, ... International Conference on Machine Learning, 7480-7512, 2023 | 481 | 2023 |
| Sigmoid loss for language image pre-training X Zhai, B Mustafa, A Kolesnikov, L Beyer Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 446 | 2023 |
| Are we done with ImageNet? L Beyer*, OJ Henaff*, A Kolesnikov*, X Zhai*, A Oord*, *equal contribution arXiv preprint arXiv:2006.07159, 2020 | 408 | 2020 |
| Knowledge distillation: A good teacher is patient and consistent L Beyer, X Zhai, A Royer, L Markeeva, R Anil, A Kolesnikov IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 | 316 | 2022 |
| On Robustness and Transferability of Convolutional Neural Networks J Djolonga, J Yung, M Tschannen, R Romijnders, L Beyer, A Kolesnikov, ... IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020 | 153 | 2020 |
| Pali-x: On scaling up a multilingual vision and language model X Chen, J Djolonga, P Padlewski, B Mustafa, S Changpinyo, J Wu, ... arXiv preprint arXiv:2305.18565, 2023 | 145 | 2023 |
| Better plain vit baselines for imagenet-1k L Beyer, X Zhai, A Kolesnikov arXiv preprint arXiv:2205.01580, 2022 | 109 | 2022 |
| Flexivit: One model for all patch sizes L Beyer, P Izmailov, A Kolesnikov, M Caron, S Kornblith, X Zhai, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 87 | 2023 |
Xiaohua ZhaiResearch Scientist, Google DeepMindEmail verificata su google.com
