iCaRL: Incremental Classifier and Representation Learning SA Rebuffi, A Kolesnikov, G Sperl, CH Lampert CVPR 2017, 2017 | 686 | 2017 |
Learning multiple visual domains with residual adapters SA Rebuffi, H Bilen, A Vedaldi NIPS 2017, 2017 | 235 | 2017 |
Efficient parametrization of multi-domain deep neural networks SA Rebuffi, H Bilen, A Vedaldi CVPR 2018, 2018 | 137 | 2018 |
Modeling of Store Gletscher's calving dynamics, West Greenland, in response to ocean thermal forcing M Morlighem, J Bondzio, H Seroussi, E Rignot, E Larour, A Humbert, ... Geophysical Research Letters 43 (6), 2659-2666, 2016 | 87 | 2016 |
There and Back Again: Revisiting Backpropagation Saliency Methods SA Rebuffi, R Fong, X Ji, A Vedaldi CVPR 2020, 2020 | 17* | 2020 |
Semi-supervised learning with scarce annotations SA Rebuffi, S Ehrhardt, K Han, A Vedaldi, A Zisserman Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2020 | 13 | 2020 |
Automatically Discovering and Learning New Visual Categories with Ranking Statistics K Han, SA Rebuffi, S Ehrhardt, A Vedaldi, A Zisserman ICLR 2020, 2020 | 11 | 2020 |
Lsd-c: Linearly separable deep clusters SA Rebuffi, S Ehrhardt, K Han, A Vedaldi, A Zisserman arXiv preprint arXiv:2006.10039, 2020 | 2 | 2020 |