Hilde Kuehne

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Thomas SerreProfessor, Brown University and ANR-3IA Artificial and Natural Intelligence Toulouse InstituteDirección de correo verificada de brown.edu
Rogerio FerisResearch Manager, MIT-IBM Watson AI LabDirección de correo verificada de us.ibm.com
Juergen GallUniversity of BonnDirección de correo verificada de iai.uni-bonn.de
James GlassMIT Computer Science and Artificial Intelligence LaboratoryDirección de correo verificada de mit.edu
Leonid KarlinskyPrincipal Research Scientist, MIT-IBM Watson AI Lab, IBM ResearchDirección de correo verificada de ibm.com
Alexander RichardResearch Scientist, Facebook Reality LabsDirección de correo verificada de fb.com
Nina ShvetsovaUniversity of BonnDirección de correo verificada de uni-frankfurt.de
Andrew RouditchenkoPhD Student at MIT CSAILDirección de correo verificada de mit.edu
Anna KuklevaMax Planck Institute for InformaticsDirección de correo verificada de mpi-inf.mpg.de
David HarwathThe University of Texas at AustinDirección de correo verificada de utexas.edu
Samuel ThomasIBM Research AIDirección de correo verificada de us.ibm.com
Felix PetersenStanford University, University of KonstanzDirección de correo verificada de stanford.edu
Oliver DeussenProfessor of Computer Science, University of Konstanz Dirección de correo verificada de uni-konstanz.de
Christian BorgeltProfessor for Data Science, Paris Lodron University of SalzburgDirección de correo verificada de borgelt.net
Rameswar PandaDistinguished Engineer, IBM ResearchDirección de correo verificada de ibm.com
Brian KingsburyDistinguished Research Staff Member and Manager, IBM T. J. Watson Research Center, Yorktown HeightsDirección de correo verificada de us.ibm.com
Huei-han JhuangPerceiving Systems, Max Planck Institute for Intelligent SystemsDirección de correo verificada de tuebingen.mpg.de
TOMASO POGGIOMcDermott Professor in Brain Sciences, MITDirección de correo verificada de ai.mit.edu
Estibaliz GarroteResearcher, TecnaliaDirección de correo verificada de tecnalia.com
Mubarak ShahTrustee Chair Professor of Computer Science, University of Central FloridaDirección de correo verificada de crcv.ucf.edu

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Hilde Kuehne

Tuebingen AI Center, University of Tuebingen, MIT-IBM Watson Lab

Dirección de correo verificada de uni-tuebingen.de - Página principal

Multimodal learning Video understanding Action Recognition Computer vision Machine learning


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
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	4880	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	731	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	259	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	243	2016
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	178*	2019
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	169	2018
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	167	2022
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	156	2020
Weakly supervised learning of actions from transcripts H Kuehne, A Richard, J Gall Computer Vision and Image Understanding 163, 78-89, 2017	149	2017
Contrastive audio-visual masked autoencoder Y Gong, A Rouditchenko, AH Liu, D Harwath, L Karlinsky, H Kuehne, ... arXiv preprint arXiv:2210.07839, 2022	142	2022
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	140	2019
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	115	2018
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	109	2018
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	105	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	69	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	63	2021
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	58	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	50	2011
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	46	2021
Match, expand and improve: Unsupervised finetuning for zero-shot action recognition with language knowledge W Lin, L Karlinsky, N Shvetsova, H Possegger, M Kozinski, R Panda, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023	42	2023

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