Alexander A. Kolesnikov
Alexander A. Kolesnikov
Google Research, Brain team.
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Cited by
Cited by
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
A Dosovitskiy*, L Beyer*, A Kolesnikov*, D Weissenborn*, X Zhai*, ...
ICLR 2021, 2020
iCaRL: Incremental Classifier and Representation Learning
SA Rebuffi, A Kolesnikov, G Sperl, CH Lampert
CVPR 2017, 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, ...
IJCV 2018, 2018
Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation
A Kolesnikov, CH Lampert
ECCV 2016, 2016
Revisiting Self-Supervised Visual Representation Learning
A Kolesnikov*, X Zhai*, L Beyer*, *equal contribtion
CVPR 2019, 2019
Big Transfer (BiT): General Visual Representation Learning
A Kolesnikov*, L Beyer*, X Zhai*, J Puigcerver, J Yung, S Gelly, ...
ECCV 2020, 2020
S4L: Self-Supervised Semi-Supervised Learning
X Zhai*, A Oliver*, A Kolesnikov*, L Beyer*, *equal contribution
ICCV 2019, 2019
MLP-Mixer: An all-MLP Architecture for Vision
I Tolstikhin*, N Houlsby*, A Kolesnikov*, L Beyer*, X Zhai, T Unterthiner, ...
NeurIPS 2021, 2021
Scaling vision transformers
X Zhai, A Kolesnikov, N Houlsby, L Beyer
arXiv preprint arXiv:2106.04560, 2021
Are we done with ImageNet?
L Beyer*, OJ Henaff*, A Kolesnikov*, X Zhai*, A Oord*, *equal contribution
arXiv preprint arXiv:2006.07159, 2020
Detecting Visual Relationships Using Box Attention
A Kolesnikov, A Kuznetsova, CH Lampert, V Ferrari
ICCV 2019 Workshop on Scene Graph Representation and Learning, 2019
PixelCNN models with Auxiliary Variables for Natural Image Modeling
A Kolesnikov, CH Lampert
ICML 2017, 2017
Probabilistic Image Colorization
A Royer*, A Kolesnikov*, CH Lampert, *equal contribution
BMVC 2017, 2017
On Robustness and Transferability of Convolutional Neural Networks
J Djolonga, J Yung, M Tschannen, R Romijnders, L Beyer, A Kolesnikov, ...
CVPR 2021, 2020
Closed-Form Training of Conditional Random Fields for Large Scale Image Segmentation
A Kolesnikov, M Guillaumin, V Ferrari, CH Lampert
ECCV 2014, 2014
The visual task adaptation benchmark
X Zhai*, J Puigcerver*, A Kolesnikov*, P Ruyssen, C Riquelme, M Lucic, ...
arXiv preprint arXiv:1910.04867, 2019
Improving Weakly-Supervised Object Localization By Micro-Annotation
A Kolesnikov, CH Lampert
BMVC 2016, 2016
How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers
A Steiner, A Kolesnikov, X Zhai, R Wightman, J Uszkoreit, L Beyer
arXiv preprint arXiv:2106.10270, 2021
Estimating barriers to gene flow from distorted isolation-by-distance patterns
H Ringbauer, A Kolesnikov, DL Field, NH Barton
Genetics 208 (3), 1231-1245, 2018
Predicting CTR of new ads via click prediction
A Kolesnikov, Y Logachev, V Topinskiy
CIKM 2012, 2012
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