| Virtual worlds as proxy for multi-object tracking analysis A Gaidon, Q Wang, Y Cabon, E Vig Computer Vision and Pattern Recognition (CVPR), 2016 IEEE Conference on, 2016 | 367 | 2016 |
| Actom sequence models for efficient action detection A Gaidon, Z Harchaoui, C Schmid CVPR 2011, 3201-3208, 2011 | 170 | 2011 |
| Temporal Localization of Actions with Actoms A Gaidon, Z Harchaoui, C Schmid Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2013 | 148 | 2013 |
| Activity representation with motion hierarchies A Gaidon, Z Harchaoui, C Schmid International journal of computer vision 107 (3), 219-238, 2014 | 94 | 2014 |
| INRIA-LEARs video copy detection system M Douze, A Gaidon, H Jegou, M Marszałek, C Schmid | 94 | 2008 |
| Recognizing activities with cluster-trees of tracklets A Gaidon, Z Harchaoui, C Schmid British Machine Vision Conference (BMVC), 2012 | 79 | 2012 |
| Procedural generation of videos to train deep action recognition networks C Roberto de Souza, A Gaidon, Y Cabon, A Manuel Lopez Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 55* | 2017 |
| Sympathy for the details: Dense trajectories and hybrid classification architectures for action recognition CR De Souza, A Gaidon, E Vig, AM López European Conference on Computer Vision, 697-716, 2016 | 41 | 2016 |
| A time series kernel for action recognition A Gaidon, Z Harchaoui, C Schmid British Machine Vision Conference (BMVC), 2011 | 37 | 2011 |
| Mining visual actions from movies A Gaidon, M Marszalek, S Cordelia British Machine Vision Conference (BMVC), 2009 | 30 | 2009 |
| Self-learning object detectors for unlabeled videos using multi-task learning A Gaidon, ZEN Gloria, JAR Serrano US Patent 9,158,971, 2015 | 28 | 2015 |
| Online learning to sample G Bouchard, T Trouillon, J Perez, A Gaidon arXiv preprint arXiv:1506.09016, 2015 | 23 | 2015 |
| Learning to fuse things and stuff J Li, A Raventos, A Bhargava, T Tagawa, A Gaidon arXiv preprint arXiv:1812.01192, 2018 | 17 | 2018 |
| Roi-10d: Monocular lifting of 2d detection to 6d pose and metric shape F Manhardt, W Kehl, A Gaidon Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019 | 16 | 2019 |
| Superdepth: Self-supervised, super-resolved monocular depth estimation S Pillai, R Ambrus, A Gaidon ICRA, 2019 | 12 | 2019 |
| Online domain adaptation for multi-object tracking A Gaidon, E Vig British Machine Vision Conference (BMVC), 2015 | 12 | 2015 |
| Self-learning camera: Autonomous adaptation of object detectors to unlabeled video streams A Gaidon, G Zen, JA Rodriguez-Serrano arXiv preprint arXiv:1406.4296, 2014 | 12 | 2014 |
| Classification aided two stage localization H Harzallah, C Schmid, F Jurie, A Gaidon PASCAL Visual Object Classes Challenge Workshop, in conjunction with ECCV, 2008 | 12 | 2008 |
| Extracting gradient features from neural networks AG Soldevila, A Gaidon, FC Perronnin US Patent 9,792,492, 2017 | 10 | 2017 |
| Spigan: Privileged adversarial learning from simulation KH Lee, G Ros, J Li, A Gaidon ICLR, 2019 | 8 | 2019 |
Cordelia SchmidResearch director INRIA Geverifieerd e-mailadres voor inria.fr
