| HMDB: a large video database for human motion recognition H Kuehne, H Jhuang, E Garrote, T Poggio, T Serre 2011 International conference on computer vision, 2556-2563, 2011 | 2307 | 2011 |
| The language of actions: Recovering the syntax and semantics of goal-directed human activities H Kuehne, A Arslan, T Serre Proceedings of the IEEE conference on computer vision and pattern …, 2014 | 242 | 2014 |
| Weakly supervised action learning with rnn based fine-to-coarse modeling A Richard, H Kuehne, J Gall Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 103 | 2017 |
| An end-to-end generative framework for video segmentation and recognition H Kuehne, J Gall, T Serre 2016 IEEE Winter Conference on Applications of Computer Vision (WACV), 1-8, 2016 | 97 | 2016 |
| Weakly supervised learning of actions from transcripts H Kuehne, A Richard, J Gall Computer Vision and Image Understanding 163, 78-89, 2017 | 59 | 2017 |
| Hmm-based human motion recognition with optical flow data D Gehrig, H Kuehne, A Woerner, T Schultz 2009 9th IEEE-RAS International Conference on Humanoid Robots, 425-430, 2009 | 49 | 2009 |
| Combined intention, activity, and motion recognition for a humanoid household robot D Gehrig, P Krauthausen, L Rybok, H Kuehne, UD Hanebeck, T Schultz, ... 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2011 | 38 | 2011 |
| Neuralnetwork-viterbi: A framework for weakly supervised video learning A Richard, H Kuehne, A Iqbal, J Gall Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 37 | 2018 |
| Action sets: Weakly supervised action segmentation without ordering constraints A Richard, H Kuehne, J Gall Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 26 | 2018 |
| More is less: Learning efficient video representations by big-little network and depthwise temporal aggregation Q Fan, CF Chen, H Kuehne, M Pistoia, D Cox arXiv preprint arXiv:1912.00869, 2019 | 13 | 2019 |
| A hybrid RNN-HMM approach for weakly supervised temporal action segmentation H Kuehne, A Richard, J Gall IEEE transactions on pattern analysis and machine intelligence 42 (4), 765-779, 2018 | 12 | 2018 |
| Unsupervised learning of action classes with continuous temporal embedding A Kukleva, H Kuehne, F Sener, J Gall Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 10 | 2019 |
| Extraction and analysis of coronary tree from single X-ray angiographies H Koehler, M Couprie, S Bouattour, D Paulus Medical Imaging 2004: Visualization, Image-Guided Procedures, and Display …, 2004 | 10 | 2004 |
| Automatic human model parametrization from 3d marker data for motion recognition T Koehler, M Pruzinec, T Feldmann, A Wörner Proceedings of WSCG, 2008 | 9 | 2008 |
| Superficial Gaussian Mixture Reduction. MF Huber, P Krauthausen, UD Hanebeck GI-Jahrestagung, 491, 2011 | 8 | 2011 |
| On-line Action Recognition from Sparse Feature Flow. H Kuehne, D Gehrig, T Schultz, R Stiefelhagen VISAPP (1), 634-639, 2012 | 7 | 2012 |
| An iterative scheme for motion-based scene segmentation A Bachmann, H Kuehne 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV …, 2009 | 7 | 2009 |
| Mining youtube-a dataset for learning fine-grained action concepts from webly supervised video data H Kuehne, A Iqbal, A Richard, J Gall arXiv preprint arXiv:1906.01012, 2019 | 5 | 2019 |
| Towards a generative approach to activity recognition and segmentation H Kuehne, T Serre CoRR, vol. abs/1509.01947, 2015 | 5 | 2015 |
| Kinematische Analyse menschlicher Alltagsbewegungen für die Mensch-Maschine-Interaktion T Stein, A Fischer, I Boesnach, D Gehrig, H Köhler, H Schwameder Sporttechnologie zwischen Theorie und Praxis: V. Aachen: Shaker, 2007 | 5 | 2007 |
Thomas SerreBrown University and ANR-3IA Artificial and Natural Intelligence Toulouse InstituteVerified email at brown.edu
