Hilde Kuehne

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Thomas SerreProfessor, Brown University and ANR-3IA Artificial and Natural Intelligence Toulouse InstituteVerified email at brown.edu
Juergen GallUniversity of BonnVerified email at iai.uni-bonn.de
Alexander RichardResearch Scientist, Facebook Reality LabsVerified email at fb.com
Rogerio FerisResearch Manager, MIT-IBM Watson AI LabVerified email at us.ibm.com
Huei-han JhuangPerceiving Systems, Max Planck Institute for Intelligent SystemsVerified email at tuebingen.mpg.de
TOMASO POGGIOMcDermott Professor in Brain Sciences, MITVerified email at ai.mit.edu
Estibaliz GarroteResearcher, TecnaliaVerified email at tecnalia.com
David HarwathThe University of Texas at AustinVerified email at utexas.edu
Andrew RouditchenkoPhD Student at MIT CSAILVerified email at mit.edu
James GlassMIT Computer Science and Artificial Intelligence LaboratoryVerified email at mit.edu
Samuel ThomasIBM Research AIVerified email at us.ibm.com
Brian KingsburyDistinguished Research Staff Member and Manager, IBM T. J. Watson Research Center, Yorktown HeightsVerified email at us.ibm.com
Anna KuklevaMax Planck Institute for InformaticsVerified email at mpi-inf.mpg.de
Tanja SchultzProfessor of Computer Science, University BremenVerified email at uni-bremen.de
Ali Bilgin Arslan, PhDKAYAKVerified email at kayak.com
Oliver DeussenProfessor of Computer Science, University of Konstanz Verified email at uni-konstanz.de
Rameswar PandaResearch Scientist, MIT-IBM Watson AI LabVerified email at ibm.com
Brian ChenColumbia UniversityVerified email at columbia.edu
Felix PetersenStanford University, University of KonstanzVerified email at stanford.edu
Christian BorgeltProfessor for Data Science, Paris Lodron University of SalzburgVerified email at borgelt.net

Hilde Kuehne

Goethe University Frankfurt , MIT-IBM Watson Lab

Verified email at em.uni-frankfurt.de - Homepage

Computer vision Machine learning Multimodal learning Video understanding


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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	3485	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	436	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	192	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	166	2016
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	108	2018
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	107	2019
Weakly supervised learning of actions from transcripts H Kuehne, A Richard, J Gall Computer Vision and Image Understanding 163, 78-89, 2017	103	2017
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	92	2020
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	74	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	65	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	55	2018
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	53	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	45	2011
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	34	2021
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	26	2021
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	20	2022
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	15	2019
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	14	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	13	2021
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	12	2021

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