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LiT: Zero-Shot Transfer with Locked-image Text Tuning


Nov 15, 2021
Xiaohua Zhai, Xiao Wang, Basil Mustafa, Andreas Steiner, Daniel Keysers, Alexander Kolesnikov, Lucas Beyer

* Xiaohua, Xiao, Basil, Andreas and Lucas contributed equally 

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How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers


Jun 18, 2021
Andreas Steiner, Alexander Kolesnikov, Xiaohua Zhai, Ross Wightman, Jakob Uszkoreit, Lucas Beyer

* Andreas, Alex, Xiaohua and Lucas contributed equally. We release more than 50'000 ViT models trained under diverse settings on various datasets. We believe this to be a treasure trove for model analysis. Available at https://github.com/google-research/vision_transformer and https://github.com/rwightman/pytorch-image-models 

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Knowledge distillation: A good teacher is patient and consistent


Jun 09, 2021
Lucas Beyer, Xiaohua Zhai, Amélie Royer, Larisa Markeeva, Rohan Anil, Alexander Kolesnikov

* Lucas, Xiaohua, Am\'elie, Larisa, and Alex contributed equally 

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Scaling Vision Transformers


Jun 08, 2021
Xiaohua Zhai, Alexander Kolesnikov, Neil Houlsby, Lucas Beyer

* Xiaohua, Alex, and Lucas contributed equally 

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MLP-Mixer: An all-MLP Architecture for Vision


May 17, 2021
Ilya Tolstikhin, Neil Houlsby, Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Thomas Unterthiner, Jessica Yung, Andreas Steiner, Daniel Keysers, Jakob Uszkoreit, Mario Lucic, Alexey Dosovitskiy

* Fixed parameter counts in Table 1 

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SI-Score: An image dataset for fine-grained analysis of robustness to object location, rotation and size


Apr 09, 2021
Jessica Yung, Rob Romijnders, Alexander Kolesnikov, Lucas Beyer, Josip Djolonga, Neil Houlsby, Sylvain Gelly, Mario Lucic, Xiaohua Zhai

* 4 pages (10 pages including references and appendix), 10 figures. Accepted at the ICLR 2021 RobustML Workshop. arXiv admin note: text overlap with arXiv:2007.08558 

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An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale


Oct 22, 2020
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, Neil Houlsby

* Fine-tuning code and pre-trained models are available at https://github.com/google-research/vision_transformer 

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On Robustness and Transferability of Convolutional Neural Networks


Jul 16, 2020
Josip Djolonga, Jessica Yung, Michael Tschannen, Rob Romijnders, Lucas Beyer, Alexander Kolesnikov, Joan Puigcerver, Matthias Minderer, Alexander D'Amour, Dan Moldovan, Sylvan Gelly, Neil Houlsby, Xiaohua Zhai, Mario Lucic


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Are we done with ImageNet?


Jun 12, 2020
Lucas Beyer, Olivier J. Hénaff, Alexander Kolesnikov, Xiaohua Zhai, Aäron van den Oord

* All five authors contributed equally. New labels at https://github.com/google-research/reassessed-imagenet 

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Large Scale Learning of General Visual Representations for Transfer


Dec 24, 2019
Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Joan Puigcerver, Jessica Yung, Sylvain Gelly, Neil Houlsby


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The Visual Task Adaptation Benchmark


Oct 01, 2019
Xiaohua Zhai, Joan Puigcerver, Alexander Kolesnikov, Pierre Ruyssen, Carlos Riquelme, Mario Lucic, Josip Djolonga, Andre Susano Pinto, Maxim Neumann, Alexey Dosovitskiy, Lucas Beyer, Olivier Bachem, Michael Tschannen, Marcin Michalski, Olivier Bousquet, Sylvain Gelly, Neil Houlsby


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S$^\mathbf{4}$L: Self-Supervised Semi-Supervised Learning


May 09, 2019
Xiaohua Zhai, Avital Oliver, Alexander Kolesnikov, Lucas Beyer

* All four authors contributed equally 

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Revisiting Self-Supervised Visual Representation Learning


Jan 25, 2019
Alexander Kolesnikov, Xiaohua Zhai, Lucas Beyer

* All three authors contributed equally. Code is available at https://github.com/google/revisiting-self-supervised 

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Detecting Visual Relationships Using Box Attention


Jul 05, 2018
Alexander Kolesnikov, Christoph H. Lampert, Vittorio Ferrari


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PixelCNN Models with Auxiliary Variables for Natural Image Modeling


Jul 01, 2017
Alexander Kolesnikov, Christoph H. Lampert

* ICML 2017 

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Probabilistic Image Colorization


May 11, 2017
Amelie Royer, Alexander Kolesnikov, Christoph H. Lampert


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iCaRL: Incremental Classifier and Representation Learning


Apr 14, 2017
Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Georg Sperl, Christoph H. Lampert

* Accepted paper at CVPR 2017 

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Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation


Aug 06, 2016
Alexander Kolesnikov, Christoph H. Lampert

* ECCV 2016 

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Improving Weakly-Supervised Object Localization By Micro-Annotation


May 18, 2016
Alexander Kolesnikov, Christoph H. Lampert


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Identifying Reliable Annotations for Large Scale Image Segmentation


Apr 28, 2015
Alexander Kolesnikov, Christoph H. Lampert


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Closed-Form Training of Conditional Random Fields for Large Scale Image Segmentation


Mar 27, 2014
Alexander Kolesnikov, Matthieu Guillaumin, Vittorio Ferrari, Christoph H. Lampert


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