Alexander Kolesnikov

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 57

Top Topics

Probabilistic Modeling

Visual Representations

Image Segmentation

Object Location

Top Venues

Publications

Lucas Beyer, Andreas Steiner, André Susano Pinto, Alexander Kolesnikov, Xiao Wang, Daniel Salz, Maxim Neumann, Ibrahim Alabdulmohsin, Michael Tschannen, Emanuele Bugliarello, Thomas Unterthiner, Daniel Keysers, Skanda Koppula, Fangyu Liu, Adam Grycner, Alexey A. Gritsenko, Neil Houlsby, Manoj Kumar, Keran Rong, Julian Eisenschlos, Rishabh Kabra, Matthias Bauer, Matko Bosnjak, Xi Chen, Matthias Minderer, Paul Voigtlaender, Ioana Bica, Ivana Balazevic, Joan Puigcerver, Pinelopi Papalampidi, Olivier J. Hénaff, Xi Xiong, Radu Soricut, Jeremiah Harmsen, Xiaohua Zhai
PaliGemma: A versatile 3B VLM for transfer. CoRR (2024)
Yue Fan, Yongqin Xian, Xiaohua Zhai, Alexander Kolesnikov, Muhammad Ferjad Naeem, Bernt Schiele, Federico Tombari
Toward a Diffusion-Based Generalist for Dense Vision Tasks. CoRR (2024)
André Susano Pinto, Alexander Kolesnikov, Yuge Shi, Lucas Beyer, Xiaohua Zhai
Tuning computer vision models with task rewards. CoRR (2023)
Lucas Beyer, Pavel Izmailov, Alexander Kolesnikov, Mathilde Caron, Simon Kornblith, Xiaohua Zhai, Matthias Minderer, Michael Tschannen, Ibrahim Alabdulmohsin, Filip Pavetic
FlexiViT: One Model for All Patch Sizes. CVPR (2023)
Mostafa Dehghani, Josip Djolonga, Basil Mustafa, Piotr Padlewski, Jonathan Heek, Justin Gilmer, Andreas Steiner, Mathilde Caron, Robert Geirhos, Ibrahim Alabdulmohsin, Rodolphe Jenatton, Lucas Beyer, Michael Tschannen, Anurag Arnab, Xiao Wang, Carlos Riquelme, Matthias Minderer, Joan Puigcerver, Utku Evci, Manoj Kumar, Sjoerd van Steenkiste, Gamaleldin F. Elsayed, Aravindh Mahendran, Fisher Yu, Avital Oliver, Fantine Huot, Jasmijn Bastings, Mark Patrick Collier, Alexey A. Gritsenko, Vighnesh Birodkar, Cristina Vasconcelos, Yi Tay, Thomas Mensink, Alexander Kolesnikov, Filip Pavetic, Dustin Tran, Thomas Kipf, Mario Lucic, Xiaohua Zhai, Daniel Keysers, Jeremiah Harmsen, Neil Houlsby
Scaling Vision Transformers to 22 Billion Parameters. CoRR (2023)
Ibrahim M. Alabdulmohsin, Xiaohua Zhai, Alexander Kolesnikov, Lucas Beyer
Getting ViT in Shape: Scaling Laws for Compute-Optimal Model Design. NeurIPS (2023)
Xiaohua Zhai, Basil Mustafa, Alexander Kolesnikov, Lucas Beyer
Sigmoid Loss for Language Image Pre-Training. CoRR (2023)
Lucas Beyer, Bo Wan, Gagan Madan, Filip Pavetic, Andreas Steiner, Alexander Kolesnikov, André Susano Pinto, Emanuele Bugliarello, Xiao Wang, Qihang Yu, Liang-Chieh Chen, Xiaohua Zhai
A Study of Autoregressive Decoders for Multi-Tasking in Computer Vision. CoRR (2023)
Xi Chen, Xiao Wang, Soravit Changpinyo, A. J. Piergiovanni, Piotr Padlewski, Daniel Salz, Sebastian Goodman, Adam Grycner, Basil Mustafa, Lucas Beyer, Alexander Kolesnikov, Joan Puigcerver, Nan Ding, Keran Rong, Hassan Akbari, Gaurav Mishra, Linting Xue, Ashish V. Thapliyal, James Bradbury, Weicheng Kuo
PaLI: A Jointly-Scaled Multilingual Language-Image Model. ICLR (2023)
Xi Chen, Xiao Wang, Lucas Beyer, Alexander Kolesnikov, Jialin Wu, Paul Voigtlaender, Basil Mustafa, Sebastian Goodman, Ibrahim Alabdulmohsin, Piotr Padlewski, Daniel Salz, Xi Xiong, Daniel Vlasic, Filip Pavetic, Keran Rong, Tianli Yu, Daniel Keysers, Xiaohua Zhai, Radu Soricut
PaLI-3 Vision Language Models: Smaller, Faster, Stronger. CoRR (2023)
André Susano Pinto, Alexander Kolesnikov, Yuge Shi, Lucas Beyer, Xiaohua Zhai
Tuning Computer Vision Models With Task Rewards. ICML (2023)
Xiaohua Zhai, Basil Mustafa, Alexander Kolesnikov, Lucas Beyer
Sigmoid Loss for Language Image Pre-Training. ICCV (2023)
Ibrahim Alabdulmohsin, Xiaohua Zhai, Alexander Kolesnikov, Lucas Beyer
Getting ViT in Shape: Scaling Laws for Compute-Optimal Model Design. CoRR (2023)
Mostafa Dehghani, Josip Djolonga, Basil Mustafa, Piotr Padlewski, Jonathan Heek, Justin Gilmer, Andreas Peter Steiner, Mathilde Caron, Robert Geirhos, Ibrahim Alabdulmohsin, Rodolphe Jenatton, Lucas Beyer, Michael Tschannen, Anurag Arnab, Xiao Wang, Carlos Riquelme Ruiz, Matthias Minderer, Joan Puigcerver, Utku Evci, Manoj Kumar, Sjoerd van Steenkiste, Gamaleldin Fathy Elsayed, Aravindh Mahendran, Fisher Yu, Avital Oliver, Fantine Huot, Jasmijn Bastings, Mark Collier, Alexey A. Gritsenko, Vighnesh Birodkar, Cristina Nader Vasconcelos, Yi Tay, Thomas Mensink, Alexander Kolesnikov, Filip Pavetic, Dustin Tran, Thomas Kipf, Mario Lucic, Xiaohua Zhai, Daniel Keysers, Jeremiah J. Harmsen, Neil Houlsby
Scaling Vision Transformers to 22 Billion Parameters. ICML (2023)
Xi Chen, Josip Djolonga, Piotr Padlewski, Basil Mustafa, Soravit Changpinyo, Jialin Wu, Carlos Riquelme Ruiz, Sebastian Goodman, Xiao Wang, Yi Tay, Siamak Shakeri, Mostafa Dehghani, Daniel Salz, Mario Lucic, Michael Tschannen, Arsha Nagrani, Hexiang Hu, Mandar Joshi, Bo Pang, Ceslee Montgomery, Paulina Pietrzyk, Marvin Ritter, A. J. Piergiovanni, Matthias Minderer, Filip Pavetic, Austin Waters, Gang Li, Ibrahim Alabdulmohsin, Lucas Beyer, Julien Amelot, Kenton Lee, Andreas Peter Steiner, Yang Li, Daniel Keysers, Anurag Arnab, Yuanzhong Xu, Keran Rong, Alexander Kolesnikov, Mojtaba Seyedhosseini, Anelia Angelova, Xiaohua Zhai, Neil Houlsby, Radu Soricut
PaLI-X: On Scaling up a Multilingual Vision and Language Model. CoRR (2023)
Xiaohua Zhai, Xiao Wang, Basil Mustafa, Andreas Steiner, Daniel Keysers, Alexander Kolesnikov, Lucas Beyer
LiT: Zero-Shot Transfer with Locked-image text Tuning. CVPR (2022)
Alexander Kolesnikov, André Susano Pinto, Lucas Beyer, Xiaohua Zhai, Jeremiah Harmsen, Neil Houlsby
UViM: A Unified Modeling Approach for Vision with Learned Guiding Codes. NeurIPS (2022)
Xi Chen, Xiao Wang, Soravit Changpinyo, A. J. Piergiovanni, Piotr Padlewski, Daniel Salz, Sebastian Goodman, Adam Grycner, Basil Mustafa, Lucas Beyer, Alexander Kolesnikov, Joan Puigcerver, Nan Ding, Keran Rong, Hassan Akbari, Gaurav Mishra, Linting Xue, Ashish Thapliyal, James Bradbury, Weicheng Kuo, Mojtaba Seyedhosseini, Chao Jia, Burcu Karagol Ayan, Carlos Riquelme, Andreas Steiner, Anelia Angelova, Xiaohua Zhai, Neil Houlsby, Radu Soricut
PaLI: A Jointly-Scaled Multilingual Language-Image Model. CoRR (2022)
Lucas Beyer, Pavel Izmailov, Alexander Kolesnikov, Mathilde Caron, Simon Kornblith, Xiaohua Zhai, Matthias Minderer, Michael Tschannen, Ibrahim Alabdulmohsin, Filip Pavetic
FlexiViT: One Model for All Patch Sizes. CoRR (2022)
Lucas Beyer, Xiaohua Zhai, Amélie Royer, Larisa Markeeva, Rohan Anil, Alexander Kolesnikov
Knowledge distillation: A good teacher is patient and consistent. CVPR (2022)
Andreas Steiner, Alexander Kolesnikov, Xiaohua Zhai, Ross Wightman, Jakob Uszkoreit, Lucas Beyer
How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers. Trans. Mach. Learn. Res. 2022 (2022)
Lucas Beyer, Xiaohua Zhai, Alexander Kolesnikov
Better plain ViT baselines for ImageNet-1k. CoRR (2022)
Alexander Kolesnikov, André Susano Pinto, Lucas Beyer, Xiaohua Zhai, Jeremiah Harmsen, Neil Houlsby
UViM: A Unified Modeling Approach for Vision with Learned Guiding Codes. CoRR (2022)
Xiaohua Zhai, Alexander Kolesnikov, Neil Houlsby, Lucas Beyer
Scaling Vision Transformers. CVPR (2022)
Xiaohua Zhai, Alexander Kolesnikov, Neil Houlsby, Lucas Beyer
Scaling Vision Transformers. CoRR (2021)
Ilya O. Tolstikhin, Neil Houlsby, Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Thomas Unterthiner, Jessica Yung, Andreas Steiner, Daniel Keysers, Jakob Uszkoreit, Mario Lucic, Alexey Dosovitskiy
MLP-Mixer: An all-MLP Architecture for Vision. NeurIPS (2021)
Jessica Yung, Rob Romijnders, Alexander Kolesnikov, Lucas Beyer, Josip Djolonga, Neil Houlsby, Sylvain Gelly, Mario Lucic, Xiaohua Zhai
SI-Score: An image dataset for fine-grained analysis of robustness to object location, rotation and size. CoRR (2021)
Xiaohua Zhai, Xiao Wang, Basil Mustafa, Andreas Steiner, Daniel Keysers, Alexander Kolesnikov, Lucas Beyer
LiT: Zero-Shot Transfer with Locked-image Text Tuning. CoRR (2021)
Lucas Beyer, Xiaohua Zhai, Amélie Royer, Larisa Markeeva, Rohan Anil, Alexander Kolesnikov
Knowledge distillation: A good teacher is patient and consistent. CoRR (2021)
Andreas Steiner, Alexander Kolesnikov, Xiaohua Zhai, Ross Wightman, Jakob Uszkoreit, Lucas Beyer
How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers. CoRR (2021)
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, Neil Houlsby
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale. ICLR (2021)
Josip Djolonga, Jessica Yung, Michael Tschannen, Rob Romijnders, Lucas Beyer, Alexander Kolesnikov, Joan Puigcerver, Matthias Minderer, Alexander D'Amour, Dan Moldovan, Sylvain Gelly, Neil Houlsby, Xiaohua Zhai, Mario Lucic
On Robustness and Transferability of Convolutional Neural Networks. CVPR (2021)
Ilya O. Tolstikhin, Neil Houlsby, Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Thomas Unterthiner, Jessica Yung, Andreas Steiner, Daniel Keysers, Jakob Uszkoreit, Mario Lucic, Alexey Dosovitskiy
MLP-Mixer: An all-MLP Architecture for Vision. CoRR (2021)
Lucas Beyer, Olivier J. Hénaff, Alexander Kolesnikov, Xiaohua Zhai, Aäron van den Oord
Are we done with ImageNet? CoRR (2020)
Josip Djolonga, Jessica Yung, Michael Tschannen, Rob Romijnders, Lucas Beyer, Alexander Kolesnikov, Joan Puigcerver, Matthias Minderer, Alexander D'Amour, Dan Moldovan, Sylvain Gelly, Neil Houlsby, Xiaohua Zhai, Mario Lucic
On Robustness and Transferability of Convolutional Neural Networks. CoRR (2020)
Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Joan Puigcerver, Jessica Yung, Sylvain Gelly, Neil Houlsby
Big Transfer (BiT): General Visual Representation Learning. ECCV (5) (2020)
Alina Kuznetsova, Hassan Rom, Neil Alldrin, Jasper R. R. Uijlings, Ivan Krasin, Jordi Pont-Tuset, Shahab Kamali, Stefan Popov, Matteo Malloci, Alexander Kolesnikov, Tom Duerig, Vittorio Ferrari
The Open Images Dataset V4. Int. J. Comput. Vis. 128 (7) (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
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale. CoRR (2020)
Alexander Kolesnikov, Alina Kuznetsova, Christoph Lampert, Vittorio Ferrari
Detecting Visual Relationships Using Box Attention. ICCV Workshops (2019)
Xiaohua Zhai, Joan Puigcerver, Alexander Kolesnikov, Pierre Ruyssen, Carlos Riquelme, Mario Lucic, Josip Djolonga, André Susano Pinto, Maxim Neumann, Alexey Dosovitskiy, Lucas Beyer, Olivier Bachem, Michael Tschannen, Marcin Michalski, Olivier Bousquet, Sylvain Gelly, Neil Houlsby
The Visual Task Adaptation Benchmark. CoRR (2019)
Alexander Kolesnikov, Xiaohua Zhai, Lucas Beyer
Revisiting Self-Supervised Visual Representation Learning. CVPR (2019)
Alexander Kolesnikov, Xiaohua Zhai, Lucas Beyer
Revisiting Self-Supervised Visual Representation Learning. CoRR (2019)
Xiaohua Zhai, Avital Oliver, Alexander Kolesnikov, Lucas Beyer
L: Self-Supervised Semi-Supervised Learning. CoRR (2019)
Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Joan Puigcerver, Jessica Yung, Sylvain Gelly, Neil Houlsby
Large Scale Learning of General Visual Representations for Transfer. CoRR (2019)
Lucas Beyer, Xiaohua Zhai, Avital Oliver, Alexander Kolesnikov
S4L: Self-Supervised Semi-Supervised Learning. ICCV (2019)
Alexander Kolesnikov, Christoph H. Lampert, Vittorio Ferrari
Detecting Visual Relationships Using Box Attention. CoRR (2018)
Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Georg Sperl, Christoph H. Lampert
iCaRL: Incremental Classifier and Representation Learning. CVPR (2017)
Amelie Royer, Alexander Kolesnikov, Christoph H. Lampert
Probabilistic Image Colorization. BMVC (2017)
Alexander Kolesnikov, Christoph H. Lampert
PixelCNN Models with Auxiliary Variables for Natural Image Modeling. ICML (2017)
Amelie Royer, Alexander Kolesnikov, Christoph H. Lampert
Probabilistic Image Colorization. CoRR (2017)
Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Christoph H. Lampert
iCaRL: Incremental Classifier and Representation Learning. CoRR (2016)
Alexander Kolesnikov, Christoph H. Lampert
Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation. ECCV (4) (2016)
Alexander Kolesnikov, Christoph H. Lampert
Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation. CoRR (2016)
Alexander Kolesnikov, Christoph H. Lampert
Improving Weakly-Supervised Object Localization By Micro-Annotation. BMVC (2016)
Alexander Kolesnikov, Christoph H. Lampert
Deep Probabilistic Modeling of Natural Images using a Pyramid Decomposition. CoRR (2016)
Alexander Kolesnikov, Christoph H. Lampert
Improving Weakly-Supervised Object Localization By Micro-Annotation. CoRR (2016)
Alexander Kolesnikov, Christoph H. Lampert
Identifying Reliable Annotations for Large Scale Image Segmentation. CoRR (2015)
Alexander Kolesnikov, Matthieu Guillaumin, Vittorio Ferrari, Christoph H. Lampert
Closed-Form Approximate CRF Training for Scalable Image Segmentation. ECCV (3) (2014)
Alexander Kolesnikov, Matthieu Guillaumin, Vittorio Ferrari, Christoph H. Lampert
Closed-Form Training of Conditional Random Fields for Large Scale Image Segmentation. CoRR (2014)