Alexander Kolesnikov

64 papers A* 19A 2Journal 39Unranked 4
YearRankTypeTitle / Venue / Authors
2025 J jnl
Jet: A Modern Transformer-Based Normalizing Flow.
Trans. Mach. Learn. Res.
Alexander Kolesnikov, André Susano Pinto, Michael Tschannen
2025 A* conf
JetFormer: An autoregressive generative model of raw images and text.
ICLR
Michael Tschannen, André Susano Pinto, Alexander Kolesnikov
2024 J jnl
Jet: A Modern Transformer-Based Normalizing Flow.
CoRR
Alexander Kolesnikov, André Susano Pinto, Michael Tschannen
2024 J jnl
JetFormer: An Autoregressive Generative Model of Raw Images and Text.
CoRR
Michael Tschannen, André Susano Pinto, Alexander Kolesnikov
2024 A* conf
On Scaling Up a Multilingual Vision and Language Model.
CVPR
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
2024 J jnl
PaliGemma: A versatile 3B VLM for transfer.
CoRR
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
2024 J jnl
Toward a Diffusion-Based Generalist for Dense Vision Tasks.
CoRR
Yue Fan, Yongqin Xian, Xiaohua Zhai, Alexander Kolesnikov, Muhammad Ferjad Naeem, Bernt Schiele, Federico Tombari
2023 J jnl
A Study of Autoregressive Decoders for Multi-Tasking in Computer Vision.
CoRR
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
2023 A* conf
FlexiViT: One Model for All Patch Sizes.
CVPR
Lucas Beyer, Pavel Izmailov, Alexander Kolesnikov, Mathilde Caron, Simon Kornblith, Xiaohua Zhai, Matthias Minderer, Michael Tschannen, Ibrahim Alabdulmohsin, Filip Pavetic
2023 A* conf
Getting ViT in Shape: Scaling Laws for Compute-Optimal Model Design.
NeurIPS
Ibrahim M. Alabdulmohsin, Xiaohua Zhai, Alexander Kolesnikov, Lucas Beyer
2023 J jnl
Getting ViT in Shape: Scaling Laws for Compute-Optimal Model Design.
CoRR
Ibrahim Alabdulmohsin, Xiaohua Zhai, Alexander Kolesnikov, Lucas Beyer
2023 J jnl
PaLI-3 Vision Language Models: Smaller, Faster, Stronger.
CoRR
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
2023 J jnl
PaLI-X: On Scaling up a Multilingual Vision and Language Model.
CoRR
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
2023 A* conf
PaLI: A Jointly-Scaled Multilingual Language-Image Model.
ICLR
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
2023 A* conf
Scaling Vision Transformers to 22 Billion Parameters.
ICML
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
2023 J jnl
Scaling Vision Transformers to 22 Billion Parameters.
CoRR
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 Nader Vasconcelos, Yi Tay, Thomas Mensink, Alexander Kolesnikov, Filip Pavetic, Dustin Tran, Thomas Kipf, Mario Lucic, Xiaohua Zhai, Daniel Keysers, Jeremiah Harmsen, Neil Houlsby
2023 A* conf
Sigmoid Loss for Language Image Pre-Training.
ICCV
Xiaohua Zhai, Basil Mustafa, Alexander Kolesnikov, Lucas Beyer
2023 J jnl
Sigmoid Loss for Language Image Pre-Training.
CoRR
Xiaohua Zhai, Basil Mustafa, Alexander Kolesnikov, Lucas Beyer
2023 A* conf
Tuning Computer Vision Models With Task Rewards.
ICML
André Susano Pinto, Alexander Kolesnikov, Yuge Shi, Lucas Beyer, Xiaohua Zhai
2023 J jnl
Tuning computer vision models with task rewards.
CoRR
André Susano Pinto, Alexander Kolesnikov, Yuge Shi, Lucas Beyer, Xiaohua Zhai
2022 J jnl
Better plain ViT baselines for ImageNet-1k.
CoRR
Lucas Beyer, Xiaohua Zhai, Alexander Kolesnikov
2022 J jnl
FlexiViT: One Model for All Patch Sizes.
CoRR
Lucas Beyer, Pavel Izmailov, Alexander Kolesnikov, Mathilde Caron, Simon Kornblith, Xiaohua Zhai, Matthias Minderer, Michael Tschannen, Ibrahim Alabdulmohsin, Filip Pavetic
2022 J jnl
How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers.
Trans. Mach. Learn. Res.
Andreas Steiner, Alexander Kolesnikov, Xiaohua Zhai, Ross Wightman, Jakob Uszkoreit, Lucas Beyer
2022 A* conf
Knowledge distillation: A good teacher is patient and consistent.
CVPR
Lucas Beyer, Xiaohua Zhai, Amélie Royer, Larisa Markeeva, Rohan Anil, Alexander Kolesnikov
2022 A* conf
LiT: Zero-Shot Transfer with Locked-image text Tuning.
CVPR
Xiaohua Zhai, Xiao Wang, Basil Mustafa, Andreas Steiner, Daniel Keysers, Alexander Kolesnikov, Lucas Beyer
2022 J jnl
PaLI: A Jointly-Scaled Multilingual Language-Image Model.
CoRR
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, Mojtaba Seyedhosseini, Chao Jia, Burcu Karagol Ayan, Carlos Riquelme, Andreas Steiner, Anelia Angelova, Xiaohua Zhai, Neil Houlsby, Radu Soricut
2022 A* conf
Scaling Vision Transformers.
CVPR
Xiaohua Zhai, Alexander Kolesnikov, Neil Houlsby, Lucas Beyer
2022 A* conf
UViM: A Unified Modeling Approach for Vision with Learned Guiding Codes.
NeurIPS
Alexander Kolesnikov, André Susano Pinto, Lucas Beyer, Xiaohua Zhai, Jeremiah Harmsen, Neil Houlsby
2022 J jnl
UViM: A Unified Modeling Approach for Vision with Learned Guiding Codes.
CoRR
Alexander Kolesnikov, André Susano Pinto, Lucas Beyer, Xiaohua Zhai, Jeremiah Harmsen, Neil Houlsby
2021 A* conf
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.
ICLR
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, Neil Houlsby
2021 J jnl
How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers.
CoRR
Andreas Steiner, Alexander Kolesnikov, Xiaohua Zhai, Ross Wightman, Jakob Uszkoreit, Lucas Beyer
2021 J jnl
Knowledge distillation: A good teacher is patient and consistent.
CoRR
Lucas Beyer, Xiaohua Zhai, Amélie Royer, Larisa Markeeva, Rohan Anil, Alexander Kolesnikov
2021 J jnl
LiT: Zero-Shot Transfer with Locked-image Text Tuning.
CoRR
Xiaohua Zhai, Xiao Wang, Basil Mustafa, Andreas Steiner, Daniel Keysers, Alexander Kolesnikov, Lucas Beyer
2021 A* conf
MLP-Mixer: An all-MLP Architecture for Vision.
NeurIPS
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
2021 J jnl
MLP-Mixer: An all-MLP Architecture for Vision.
CoRR
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
2021 A* conf
On Robustness and Transferability of Convolutional Neural Networks.
CVPR
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
2021 J jnl
SI-Score: An image dataset for fine-grained analysis of robustness to object location, rotation and size.
CoRR
Jessica Yung, Rob Romijnders, Alexander Kolesnikov, Lucas Beyer, Josip Djolonga, Neil Houlsby, Sylvain Gelly, Mario Lucic, Xiaohua Zhai
2021 J jnl
Scaling Vision Transformers.
CoRR
Xiaohua Zhai, Alexander Kolesnikov, Neil Houlsby, Lucas Beyer
2020 J jnl
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.
CoRR
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, Neil Houlsby
2020 J jnl
Are we done with ImageNet?
CoRR
Lucas Beyer, Olivier J. Hénaff, Alexander Kolesnikov, Xiaohua Zhai, Aäron van den Oord
2020 — conf
Big Transfer (BiT): General Visual Representation Learning.
ECCV (5)
Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Joan Puigcerver, Jessica Yung, Sylvain Gelly, Neil Houlsby
2020 J jnl
On Robustness and Transferability of Convolutional Neural Networks.
CoRR
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
2020 J jnl
The Open Images Dataset V4.
Int. J. Comput. Vis.
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
2019 — conf
Detecting Visual Relationships Using Box Attention.
ICCV Workshops
Alexander Kolesnikov, Alina Kuznetsova, Christoph Lampert, Vittorio Ferrari
2019 J jnl
Large Scale Learning of General Visual Representations for Transfer.
CoRR
Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Joan Puigcerver, Jessica Yung, Sylvain Gelly, Neil Houlsby
2019 A* conf
Revisiting Self-Supervised Visual Representation Learning.
CVPR
Alexander Kolesnikov, Xiaohua Zhai, Lucas Beyer
2019 J jnl
Revisiting Self-Supervised Visual Representation Learning.
CoRR
Alexander Kolesnikov, Xiaohua Zhai, Lucas Beyer
2019 J jnl
S
CoRR
Xiaohua Zhai, Avital Oliver, Alexander Kolesnikov, Lucas Beyer
2019 A* conf
S4L: Self-Supervised Semi-Supervised Learning.
ICCV
Lucas Beyer, Xiaohua Zhai, Avital Oliver, Alexander Kolesnikov
2019 J jnl
The Visual Task Adaptation Benchmark.
CoRR
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
2018 J jnl
Detecting Visual Relationships Using Box Attention.
CoRR
Alexander Kolesnikov, Christoph H. Lampert, Vittorio Ferrari
2017 A* conf
PixelCNN Models with Auxiliary Variables for Natural Image Modeling.
ICML
Alexander Kolesnikov, Christoph H. Lampert
2017 A conf
Probabilistic Image Colorization.
BMVC
Amelie Royer, Alexander Kolesnikov, Christoph H. Lampert
2017 J jnl
Probabilistic Image Colorization.
CoRR
Amelie Royer, Alexander Kolesnikov, Christoph H. Lampert
2017 A* conf
iCaRL: Incremental Classifier and Representation Learning.
CVPR
Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Georg Sperl, Christoph H. Lampert
2016 J jnl
Deep Probabilistic Modeling of Natural Images using a Pyramid Decomposition.
CoRR
Alexander Kolesnikov, Christoph H. Lampert
2016 A conf
Improving Weakly-Supervised Object Localization By Micro-Annotation.
BMVC
Alexander Kolesnikov, Christoph H. Lampert
2016 J jnl
Improving Weakly-Supervised Object Localization By Micro-Annotation.
CoRR
Alexander Kolesnikov, Christoph H. Lampert
2016 — conf
Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation.
ECCV (4)
Alexander Kolesnikov, Christoph H. Lampert
2016 J jnl
Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation.
CoRR
Alexander Kolesnikov, Christoph H. Lampert
2016 J jnl
iCaRL: Incremental Classifier and Representation Learning.
CoRR
Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Christoph H. Lampert
2015 J jnl
Identifying Reliable Annotations for Large Scale Image Segmentation.
CoRR
Alexander Kolesnikov, Christoph H. Lampert
2014 — conf
Closed-Form Approximate CRF Training for Scalable Image Segmentation.
ECCV (3)
Alexander Kolesnikov, Matthieu Guillaumin, Vittorio Ferrari, Christoph H. Lampert
2014 J jnl
Closed-Form Training of Conditional Random Fields for Large Scale Image Segmentation.
CoRR
Alexander Kolesnikov, Matthieu Guillaumin, Vittorio Ferrari, Christoph H. Lampert