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Alexander Kolesnikov 0003
Person information
- affiliation: Google Research, Zurich, Switzerland
- affiliation (former): Institute of Science and Technology Austria, Klosterneuburg, Austria
Other persons with the same name
- Alexander Kolesnikov 0001 — University of Eastern Finland, Joensuu, Finland
- Alexander Kolesnikov 0002 — Yandex, Moscow, Russian Fed.
- Alexander Kolesnikov 0004 — Joint Institute for Nuclear Research, Dubna, Russia
- Alexander Kolesnikov 0005 — National Research University Higher School of Economics, Moscow, Russia
- Alexander Kolesnikov 0006 — Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
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2020 – today
- 2025
- [j3]Alexander Kolesnikov, André Susano Pinto, Michael Tschannen:
Jet: A Modern Transformer-Based Normalizing Flow. Trans. Mach. Learn. Res. 2025 (2025) - [c25]Michael Tschannen, André Susano Pinto, Alexander Kolesnikov:
JetFormer: An autoregressive generative model of raw images and text. ICLR 2025 - 2024
- [c24]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:
On Scaling Up a Multilingual Vision and Language Model. CVPR 2024: 14432-14444 - [i36]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 abs/2407.00503 (2024) - [i35]Lucas Beyer, Andreas Steiner, André Susano Pinto, Alexander Kolesnikov, Xiao Wang, Daniel Salz, Maxim Neumann
, Ibrahim Alabdulmohsin, Michael Tschannen, Emanuele Bugliarello, Thomas Unterthiner
PaliGemma: A versatile 3B VLM for transfer. CoRR abs/2407.07726 (2024) - [i34]Michael Tschannen, André Susano Pinto, Alexander Kolesnikov:
JetFormer: An Autoregressive Generative Model of Raw Images and Text. CoRR abs/2411.19722 (2024) - [i33]Alexander Kolesnikov, André Susano Pinto, Michael Tschannen:
Jet: A Modern Transformer-Based Normalizing Flow. CoRR abs/2412.15129 (2024) - 2023
- [c23]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: 14496-14506 - [c22]Xiaohua Zhai, Basil Mustafa, Alexander Kolesnikov, Lucas Beyer:
Sigmoid Loss for Language Image Pre-Training. ICCV 2023: 11941-11952 - [c21]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 - [c20]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: 7480-7512 - [c19]André Susano Pinto, Alexander Kolesnikov, Yuge Shi, Lucas Beyer, Xiaohua Zhai:
Tuning Computer Vision Models With Task Rewards. ICML 2023: 33229-33239 - [c18]Ibrahim M. Alabdulmohsin, Xiaohua Zhai, Alexander Kolesnikov, Lucas Beyer:
Getting ViT in Shape: Scaling Laws for Compute-Optimal Model Design. NeurIPS 2023 - [i32]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
Scaling Vision Transformers to 22 Billion Parameters. CoRR abs/2302.05442 (2023) - [i31]André Susano Pinto, Alexander Kolesnikov, Yuge Shi, Lucas Beyer, Xiaohua Zhai:
Tuning computer vision models with task rewards. CoRR abs/2302.08242 (2023) - [i30]Xiaohua Zhai, Basil Mustafa, Alexander Kolesnikov, Lucas Beyer:
Sigmoid Loss for Language Image Pre-Training. CoRR abs/2303.15343 (2023) - [i29]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 abs/2303.17376 (2023) - [i28]Ibrahim Alabdulmohsin, Xiaohua Zhai, Alexander Kolesnikov, Lucas Beyer:
Getting ViT in Shape: Scaling Laws for Compute-Optimal Model Design. CoRR abs/2305.13035 (2023) - [i27]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 abs/2305.18565 (2023) - [i26]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 abs/2310.09199 (2023) - 2022
- [j2]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) - [c17]Xiaohua Zhai, Alexander Kolesnikov, Neil Houlsby, Lucas Beyer:
Scaling Vision Transformers. CVPR 2022: 1204-1213 - [c16]Lucas Beyer, Xiaohua Zhai, Amélie Royer, Larisa Markeeva, Rohan Anil, Alexander Kolesnikov:
Knowledge distillation: A good teacher is patient and consistent. CVPR 2022: 10915-10924 - [c15]Xiaohua Zhai, Xiao Wang
LiT: Zero-Shot Transfer with Locked-image text Tuning. CVPR 2022: 18102-18112 - [c14]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 - [i25]Lucas Beyer, Xiaohua Zhai, Alexander Kolesnikov:
Better plain ViT baselines for ImageNet-1k. CoRR abs/2205.01580 (2022) - [i24]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 abs/2205.10337 (2022) - [i23]Xi Chen, Xiao Wang
PaLI: A Jointly-Scaled Multilingual Language-Image Model. CoRR abs/2209.06794 (2022) - [i22]Lucas Beyer, Pavel Izmailov
FlexiViT: One Model for All Patch Sizes. CoRR abs/2212.08013 (2022) - 2021
- [c13]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: 16458-16468 - [c12]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 - [c11]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: 24261-24272 - [i21]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 abs/2104.04191 (2021) - [i20]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 abs/2105.01601 (2021) - [i19]Xiaohua Zhai, Alexander Kolesnikov, Neil Houlsby, Lucas Beyer:
Scaling Vision Transformers. CoRR abs/2106.04560 (2021) - [i18]Lucas Beyer, Xiaohua Zhai, Amélie Royer, Larisa Markeeva, Rohan Anil, Alexander Kolesnikov:
Knowledge distillation: A good teacher is patient and consistent. CoRR abs/2106.05237 (2021) - [i17]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 abs/2106.10270 (2021) - [i16]Xiaohua Zhai, Xiao Wang, Basil Mustafa, Andreas Steiner, Daniel Keysers, Alexander Kolesnikov, Lucas Beyer:
LiT: Zero-Shot Transfer with Locked-image Text Tuning. CoRR abs/2111.07991 (2021) - 2020
- [j1]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): 1956-1981 (2020) - [c10]Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Joan Puigcerver, Jessica Yung, Sylvain Gelly, Neil Houlsby:
Big Transfer (BiT): General Visual Representation Learning. ECCV (5) 2020: 491-507 - [i15]Lucas Beyer, Olivier J. Hénaff, Alexander Kolesnikov, Xiaohua Zhai, Aäron van den Oord:
Are we done with ImageNet? CoRR abs/2006.07159 (2020) - [i14]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 abs/2007.08558 (2020) - [i13]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 abs/2010.11929 (2020)
2010 – 2019
- 2019
- [c9]Alexander Kolesnikov, Xiaohua Zhai, Lucas Beyer:
Revisiting Self-Supervised Visual Representation Learning. CVPR 2019: 1920-1929 - [c8]Lucas Beyer, Xiaohua Zhai, Avital Oliver, Alexander Kolesnikov:
S4L: Self-Supervised Semi-Supervised Learning. ICCV 2019: 1476-1485 - [c7]Alexander Kolesnikov, Alina Kuznetsova, Christoph Lampert, Vittorio Ferrari:
Detecting Visual Relationships Using Box Attention. ICCV Workshops 2019: 1749-1753 - [i12]Alexander Kolesnikov, Xiaohua Zhai, Lucas Beyer:
Revisiting Self-Supervised Visual Representation Learning. CoRR abs/1901.09005 (2019) - [i11]Xiaohua Zhai, Avital Oliver, Alexander Kolesnikov, Lucas Beyer:
S4L: Self-Supervised Semi-Supervised Learning. CoRR abs/1905.03670 (2019) - [i10]Xiaohua Zhai, Joan Puigcerver, Alexander Kolesnikov, Pierre Ruyssen, Carlos Riquelme, Mario Lucic, Josip Djolonga, André Susano Pinto, Maxim Neumann
The Visual Task Adaptation Benchmark. CoRR abs/1910.04867 (2019) - [i9]Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Joan Puigcerver, Jessica Yung, Sylvain Gelly, Neil Houlsby:
Large Scale Learning of General Visual Representations for Transfer. CoRR abs/1912.11370 (2019) - 2018
- [i8]Alexander Kolesnikov, Christoph H. Lampert, Vittorio Ferrari:
Detecting Visual Relationships Using Box Attention. CoRR abs/1807.02136 (2018) - 2017
- [c6]Amelie Royer, Alexander Kolesnikov, Christoph H. Lampert:
Probabilistic Image Colorization. BMVC 2017 - [c5]Sylvestre-Alvise Rebuffi
iCaRL: Incremental Classifier and Representation Learning. CVPR 2017: 5533-5542 - [c4]Alexander Kolesnikov, Christoph H. Lampert:
PixelCNN Models with Auxiliary Variables for Natural Image Modeling. ICML 2017: 1905-1914 - [i7]Amelie Royer, Alexander Kolesnikov, Christoph H. Lampert:
Probabilistic Image Colorization. CoRR abs/1705.04258 (2017) - 2016
- [c3]Alexander Kolesnikov, Christoph H. Lampert:
Improving Weakly-Supervised Object Localization By Micro-Annotation. BMVC 2016 - [c2]Alexander Kolesnikov, Christoph H. Lampert:
Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation. ECCV (4) 2016: 695-711 - [i6]Alexander Kolesnikov, Christoph H. Lampert:
Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation. CoRR abs/1603.06098 (2016) - [i5]Alexander Kolesnikov, Christoph H. Lampert:
Improving Weakly-Supervised Object Localization By Micro-Annotation. CoRR abs/1605.05538 (2016) - [i4]Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Christoph H. Lampert:
iCaRL: Incremental Classifier and Representation Learning. CoRR abs/1611.07725 (2016) - [i3]Alexander Kolesnikov, Christoph H. Lampert:
Deep Probabilistic Modeling of Natural Images using a Pyramid Decomposition. CoRR abs/1612.08185 (2016) - 2015
- [i2]Alexander Kolesnikov, Christoph H. Lampert:
Identifying Reliable Annotations for Large Scale Image Segmentation. CoRR abs/1504.07460 (2015) - 2014
- [c1]Alexander Kolesnikov, Matthieu Guillaumin, Vittorio Ferrari, Christoph H. Lampert:
Closed-Form Approximate CRF Training for Scalable Image Segmentation. ECCV (3) 2014: 550-565 - [i1]Alexander Kolesnikov, Matthieu Guillaumin, Vittorio Ferrari, Christoph H. Lampert:
Closed-Form Training of Conditional Random Fields for Large Scale Image Segmentation. CoRR abs/1403.7057 (2014)
Coauthor Index
Ibrahim Alabdulmohsin
aka: Ibrahim M. Alabdulmohsin
aka: Ibrahim M. Alabdulmohsin
Christoph H. Lampert
aka: Christoph Lampert
aka: Christoph Lampert
Andreas Steiner 0001
aka: Andreas Peter Steiner
aka: Andreas Peter Steiner
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