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Hilde Kuehne
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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
37252011
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
4782014
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
2042017
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
1782016
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
1212018
More is less: Learning efficient video representations by big-little network and depthwise temporal aggregation
Q Fan, CFR Chen, H Kuehne, M Pistoia, D Cox
Advances in Neural Information Processing Systems 32, 2019
1162019
Weakly supervised learning of actions from transcripts
H Kuehne, A Richard, J Gall
Computer Vision and Image Understanding 163, 78-89, 2017
1122017
Avlnet: Learning audio-visual language representations from instructional videos
A Rouditchenko, A Boggust, D Harwath, B Chen, D Joshi, S Thomas, ...
arXiv preprint arXiv:2006.09199, 2020
1062020
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
832018
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
782019
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
642018
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
542009
Everything at once-multi-modal fusion transformer for video retrieval
N Shvetsova, B Chen, A Rouditchenko, S Thomas, B Kingsbury, RS Feris, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
512022
Multimodal clustering networks for self-supervised learning from unlabeled videos
B Chen, A Rouditchenko, K Duarte, H Kuehne, S Thomas, A Boggust, ...
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021
472021
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
452011
Joint visual-temporal embedding for unsupervised learning of actions in untrimmed sequences
RG VidalMata, WJ Scheirer, A Kukleva, D Cox, H Kuehne
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2021
312021
Generalized and incremental few-shot learning by explicit learning and calibration without forgetting
A Kukleva, H Kuehne, B Schiele
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021
272021
Found a reason for me? weakly-supervised grounded visual question answering using capsules
A Urooj, H Kuehne, K Duarte, C Gan, N Lobo, M Shah
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
19*2021
Learning with algorithmic supervision via continuous relaxations
F Petersen, C Borgelt, H Kuehne, O Deussen
Advances in Neural Information Processing Systems 34, 16520-16531, 2021
172021
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
162019
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