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Learning with Algorithmic Supervision via Continuous Relaxations


Oct 11, 2021
Felix Petersen, Christian Borgelt, Hilde Kuehne, Oliver Deussen

* Published at NeurIPS 2021 

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Generalized and Incremental Few-Shot Learning by Explicit Learning and Calibration without Forgetting


Aug 18, 2021
Anna Kukleva, Hilde Kuehne, Bernt Schiele

* ICCV 2021 

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Found a Reason for me? Weakly-supervised Grounded Visual Question Answering using Capsules


May 11, 2021
Aisha Urooj Khan, Hilde Kuehne, Kevin Duarte, Chuang Gan, Niels Lobo, Mubarak Shah

* IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021 

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Differentiable Sorting Networks for Scalable Sorting and Ranking Supervision


May 09, 2021
Felix Petersen, Christian Borgelt, Hilde Kuehne, Oliver Deussen


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Multimodal Clustering Networks for Self-supervised Learning from Unlabeled Videos


May 05, 2021
Brian Chen, Andrew Rouditchenko, Kevin Duarte, Hilde Kuehne, Samuel Thomas, Angie Boggust, Rameswar Panda, Brian Kingsbury, Rogerio Feris, David Harwath, James Glass, Michael Picheny, Shih-Fu Chang


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Unsupervised Discriminative Embedding for Sub-Action Learning in Complex Activities


Apr 30, 2021
Sirnam Swetha, Hilde Kuehne, Yogesh S Rawat, Mubarak Shah


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Detector-Free Weakly Supervised Grounding by Separation


Apr 20, 2021
Assaf Arbelle, Sivan Doveh, Amit Alfassy, Joseph Shtok, Guy Lev, Eli Schwartz, Hilde Kuehne, Hila Barak Levi, Prasanna Sattigeri, Rameswar Panda, Chun-Fu Chen, Alex Bronstein, Kate Saenko, Shimon Ullman, Raja Giryes, Rogerio Feris, Leonid Karlinsky


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Joint Visual-Temporal Embedding for Unsupervised Learning of Actions in Untrimmed Sequences


Feb 06, 2020
Rosaura G. VidalMata, Walter J. Scheirer, Hilde Kuehne


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More Is Less: Learning Efficient Video Representations by Big-Little Network and Depthwise Temporal Aggregation


Dec 02, 2019
Quanfu Fan, Chun-Fu Chen, Hilde Kuehne, Marco Pistoia, David Cox

* Accepted at NeurIPS 2019, codes and models are available at https://github.com/IBM/bLVNet-TAM 

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A Hybrid RNN-HMM Approach for Weakly Supervised Temporal Action Segmentation


Jun 03, 2019
Hilde Kuehne, Alexander Richard, Juergen Gall

* 15 pages, preprint for IEEE TPAMI https://ieeexplore.ieee.org/document/8585084 (open access). arXiv admin note: substantial text overlap with arXiv:1703.08132 

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Mining YouTube - A dataset for learning fine-grained action concepts from webly supervised video data


Jun 03, 2019
Hilde Kuehne, Ahsan Iqbal, Alexander Richard, Juergen Gall

* 9 pages 

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Unsupervised learning of action classes with continuous temporal embedding


Apr 08, 2019
Anna Kukleva, Hilde Kuehne, Fadime Sener, Juergen Gall

* CVPR 2019 

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NeuralNetwork-Viterbi: A Framework for Weakly Supervised Video Learning


May 17, 2018
Alexander Richard, Hilde Kuehne, Ahsan Iqbal, Juergen Gall

* CVPR 2018 

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Action Sets: Weakly Supervised Action Segmentation without Ordering Constraints


May 17, 2018
Alexander Richard, Hilde Kuehne, Juergen Gall

* CVPR 2018 

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Weakly Supervised Action Learning with RNN based Fine-to-coarse Modeling


Oct 09, 2017
Alexander Richard, Hilde Kuehne, Juergen Gall


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Recurrent Residual Learning for Action Recognition


Jun 27, 2017
Ahsan Iqbal, Alexander Richard, Hilde Kuehne, Juergen Gall


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Weakly supervised learning of actions from transcripts


Jun 19, 2017
Hilde Kuehne, Alexander Richard, Juergen Gall

* 33 pages, 9 figures, to appear in CVIU 

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Cooking in the kitchen: Recognizing and Segmenting Human Activities in Videos


Mar 17, 2016
Hilde Kuehne, Juergen Gall, Thomas Serre

* 15 pages, 12 figures 

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An end-to-end generative framework for video segmentation and recognition


Mar 17, 2016
Hilde Kuehne, Juergen Gall, Thomas Serre

* Proc. of IEEE Winter Conference on Applications of Computer Vision (WACV), 2016 

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