Scaling vision with sparse mixture of experts C Riquelme, J Puigcerver, B Mustafa, M Neumann, R Jenatton, ... Advances in Neural Information Processing Systems 34, 8583-8595, 2021 | 456 | 2021 |
A large-scale study of representation learning with the visual task adaptation benchmark X Zhai, J Puigcerver, A Kolesnikov, P Ruyssen, C Riquelme, M Lucic, ... arXiv preprint arXiv:1910.04867, 2019 | 336 | 2019 |
The visual task adaptation benchmark X Zhai, J Puigcerver, A Kolesnikov, P Ruyssen, C Riquelme, M Lucic, ... | 76 | 2019 |
In-domain representation learning for remote sensing M Neumann, AS Pinto, X Zhai, N Houlsby arXiv preprint arXiv:1911.06721, 2019 | 65 | 2019 |
Uvim: A unified modeling approach for vision with learned guiding codes A Kolesnikov, A Susano Pinto, L Beyer, X Zhai, J Harmsen, N Houlsby Advances in Neural Information Processing Systems 35, 26295-26308, 2022 | 63 | 2022 |
Scalable Transfer Learning with Expert Models J Puigcerver, C Riquelme, B Mustafa, C Renggli, AS Pinto, S Gelly, ... arXiv preprint arXiv:2009.13239, 2020 | 63 | 2020 |
Learning to Merge Tokens in Vision Transformers C Renggli, AS Pinto, N Houlsby, B Mustafa, J Puigcerver, C Riquelme arXiv preprint arXiv:2202.12015, 2022 | 54 | 2022 |
Tuning computer vision models with task rewards AS Pinto, A Kolesnikov, Y Shi, L Beyer, X Zhai International Conference on Machine Learning, 33229-33239, 2023 | 31 | 2023 |
Scaling vision with sparse mixture of experts CR Ruiz, J Puigcerver, B Mustafa, M Neumann, R Jenatton, AS Pinto, ... Advances in Neural Information Processing Systems, 2021 | 25 | 2021 |
Which model to transfer? finding the needle in the growing haystack C Renggli, AS Pinto, L Rimanic, J Puigcerver, C Riquelme, C Zhang, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 19 | 2022 |
PaliGemma: A versatile 3B VLM for transfer L Beyer, A Steiner, AS Pinto, A Kolesnikov, X Wang, D Salz, M Neumann, ... arXiv preprint arXiv:2407.07726, 2024 | 18 | 2024 |
Training general representations for remote sensing using in-domain knowledge M Neumann, AS Pinto, X Zhai, N Houlsby IGARSS 2020-2020 IEEE International Geoscience and Remote Sensing Symposium …, 2020 | 17 | 2020 |
Deep Ensembles for Low-Data Transfer Learning B Mustafa, C Riquelme, J Puigcerver, AS Pinto, D Keysers, N Houlsby arXiv preprint arXiv:2010.06866, 2020 | 16 | 2020 |
Adaptive Collapsing on Bounding Volume Hierarchies for Ray-Tracing A Susano Pinto | 7* | 2010 |
A Study of Autoregressive Decoders for Multi-Tasking in Computer Vision L Beyer, B Wan, G Madan, F Pavetic, A Steiner, A Kolesnikov, AS Pinto, ... arXiv preprint arXiv:2303.17376, 2023 | 5 | 2023 |
Novelty detection using graphical models for semantic room classification A Susano Pinto, A Pronobis, L Reis Progress in Artificial Intelligence, 326-339, 2011 | 5* | 2011 |
LocCa: Visual Pretraining with Location-aware Captioners B Wan, M Tschannen, Y Xian, F Pavetic, I Alabdulmohsin, X Wang, ... arXiv preprint arXiv:2403.19596, 2024 | 2 | 2024 |
Novelty Detection for Semantic Place Categorization A Susano Pinto | | 2011 |