| iCaRL: Incremental Classifier and Representation Learning SA Rebuffi, A Kolesnikov, G Sperl, CH Lampert CVPR 2017, 2017 | 687 | 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, ... arXiv preprint arXiv:1811.00982, 2018 | 519* | 2018 |
| Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation A Kolesnikov, CH Lampert ECCV 2016, 2016 | 359 | 2016 |
| Revisiting Self-Supervised Visual Representation Learning A Kolesnikov*, X Zhai*, L Beyer*, *equal contribtion CVPR 2019, 2019 | 239 | 2019 |
| S4L: Self-Supervised Semi-Supervised Learning X Zhai*, A Oliver*, A Kolesnikov*, L Beyer*, *equal contribution ICCV 2019, 2019 | 175 | 2019 |
| Big Transfer (BiT): General Visual Representation Learning A Kolesnikov*, L Beyer*, X Zhai*, J Puigcerver, J Yung, S Gelly, ... ECCV 2020, 2020 | 100* | 2020 |
| An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale A Dosovitskiy*, L Beyer*, A Kolesnikov*, D Weissenborn*, X Zhai*, ... arXiv preprint arXiv:2010.11929, 2020 | 65 | 2020 |
| PixelCNN models with Auxiliary Variables for Natural Image Modeling A Kolesnikov, CH Lampert ICML 2017, 2017 | 36* | 2017 |
| Detecting Visual Relationships Using Box Attention A Kolesnikov, A Kuznetsova, CH Lampert, V Ferrari ICCV 2019 Workshop on Scene Graph Representation and Learning, 2019 | 30 | 2019 |
| Closed-Form Training of Conditional Random Fields for Large Scale Image Segmentation A Kolesnikov, M Guillaumin, V Ferrari, CH Lampert ECCV 2014, 2014 | 30* | 2014 |
| Probabilistic Image Colorization A Royer*, A Kolesnikov*, CH Lampert, *equal contribution BMVC 2017, 2017 | 21 | 2017 |
| The visual task adaptation benchmark X Zhai*, J Puigcerver*, A Kolesnikov*, P Ruyssen, C Riquelme, M Lucic, ... arXiv preprint arXiv:1910.04867, 2019 | 20 | 2019 |
| Improving Weakly-Supervised Object Localization By Micro-Annotation A Kolesnikov, CH Lampert BMVC 2016, 2016 | 18 | 2016 |
| 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 | 17 | 2018 |
| Predicting CTR of new ads via click prediction A Kolesnikov, Y Logachev, V Topinskiy CIKM 2012, 2012 | 10 | 2012 |
| On Robustness and Transferability of Convolutional Neural Networks J Djolonga, J Yung, M Tschannen, R Romijnders, L Beyer, A Kolesnikov, ... arXiv preprint arXiv:2007.08558, 2020 | 7 | 2020 |
| Are we done with ImageNet? L Beyer*, OJ Henaff*, A Kolesnikov*, X Zhai*, A Oord*, *equal contribution arXiv preprint arXiv:2006.07159, 2020 | 7 | 2020 |
| Identifying Reliable Annotations for Large Scale Image Segmentation A Kolesnikov, CH Lampert | | 2015 |
Christoph H. LampertProfessor at IST AustriaVerified email at ist.ac.at
