Timo Milbich

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Björn OmmerProfessor, Computer Vision & Learning Group (CompVis), University of MunichVerified email at lmu.de
Karsten RothELLIS, IMPRS-IS, University of TübingenVerified email at uni-tuebingen.de
Joseph Paul CohenAmazon, AIMI (Stanford University), Mila (Quebec AI Institute)Verified email at stanford.edu
Andreas BlattmannResearch Scientist, Black Forest LabsVerified email at blackforestlabs.ai
Samarth SinhaUniversity of TorontoVerified email at mail.utoronto.ca
Michael DorkenwaldPhD candidate at University of AmsterdamVerified email at uva.nl
Dr. Marzyeh GhassemiAssociate Professor, EECS/IMES, MITVerified email at mit.edu
Prateek GuptaDPhil, University of Oxford, The Alan Turing Institute, Montréal Institute of Learning AlgorithmsVerified email at columbia.edu
Leonard BereskaUniversity of AmsterdamVerified email at uva.nl
David PfeifferZoox IncVerified email at dltmail.de
Homanga BharadhwajCarnegie Mellon UniversityVerified email at cs.cmu.edu
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARVerified email at umontreal.ca
Robin RombachLMU MunichVerified email at lrz.uni-muenchen.de
Konstantinos G. DerpanisYork University and Samsung AI Centre TorontoVerified email at eecs.yorku.ca
Lukas RuffAignosticsVerified email at aignostics.com
Dima KotovenkoLudwig Maximilian University of MunichVerified email at lrz.uni-muenchen.de
Biagio BrattoliResearch scientist at Lunit, previously AWS. PhD at Heidelberg UniversityVerified email at lunit.io
Johannes HauxHead of AI @ askuiVerified email at askui.com
Ludwig SchmidtStanford University and AnthropicVerified email at cs.washington.edu
Miguel Angel BautistaApple Machine Learning Research (MLR)Verified email at apple.com

Timo Milbich

Aignostics GmbH

Verified email at aignostics.com - Homepage

Computer Vision Representation Learning Digital Pathology Self-supervised Learning


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Revisiting training strategies and generalization performance in deep metric learning K Roth, T Milbich, S Sinha, P Gupta, B Ommer, JP Cohen International Conference on Machine Learning, 8242-8252, 2020	211	2020
Unsupervised part-based disentangling of object shape and appearance D Lorenz, L Bereska, T Milbich, B Ommer Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019	177	2019
Diva: Diverse visual feature aggregation for deep metric learning T Milbich, K Roth, H Bharadhwaj, S Sinha, Y Bengio, B Ommer, JP Cohen Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020	71	2020
Stochastic Image-to-Video Synthesis using cINNs M Dorkenwald, T Milbich, A Blattmann, R Rombach, KG Derpanis, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021	62	2021
PADS: Policy-Adapted Sampling for Visual Similarity Learning K Roth, T Milbich, B Ommer Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020	56	2020
Simultaneous Similarity-based Self-Distillation for Deep Metric Learning K Roth, T Milbich, B Ommer, JP Cohen, M Ghassemi International Conference on Machine Learning, 9095-9106, 2021	51	2021
May I enter the roundabout? A time-to-contact computation based on stereo-vision M Muffert, T Milbich, D Pfeiffer, U Franke 2012 IEEE Intelligent Vehicles Symposium, 565-570, 2012	43	2012
Understanding Object Dynamics for Interactive Image-to-Video Synthesis A Blattmann, T Milbich, M Dorkenwald, B Ommer Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021	40	2021
iPOKE: Poking a Still Image for Controlled Stochastic Video Synthesis A Blattmann, T Milbich, M Dorkenwald, B Ommer Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021	34	2021
Sharing Matters for Generalization in Deep Metric Learning T Milbich, K Roth, B Brattoli, B Ommer IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020	30	2020
Towards learning a realistic rendering of human behavior P Esser, J Haux, T Milbich Proceedings of the European Conference on Computer Vision (ECCV) Workshops, 0-0, 2018	28	2018
Characterizing generalization under out-of-distribution shifts in deep metric learning T Milbich, K Roth, S Sinha, L Schmidt, M Ghassemi, B Ommer Advances in Neural Information Processing Systems 34, 25006-25018, 2021	25	2021
Unsupervised video understanding by reconciliation of posture similarities T Milbich, M Bautista, E Sutter, B Ommer Proceedings of the IEEE International Conference on Computer Vision, 4394-4404, 2017	23	2017
RudolfV: a foundation model by pathologists for pathologists J Dippel, B Feulner, T Winterhoff, T Milbich, S Tietz, S Schallenberg, ... arXiv preprint arXiv:2401.04079, 2024	22	2024
Behavior-Driven Synthesis of Human Dynamics A Blattmann, T Milbich, M Dorkenwald, B Ommer Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021	14	2021
Unsupervised Representation Learning by Discovering Reliable Image Relations T Milbich, O Ghori, F Diego, B Ommer Pattern Recognition 102, 107107, 2020	10	2020
Less is more: Video trimming for action recognition B Antic, T Milbich, B Ommer Proceedings of the IEEE International Conference on Computer Vision …, 2013	10	2013
Cross-Image-Attention for Conditional Embeddings in Deep Metric Learning D Kotovenko, P Ma, T Milbich, B Ommer Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023	8	2023
S2SD: Simultaneous Similarity-based Self-Distillation for Deep Metric Learning K Roth, T Milbich, B Ommer, JP Cohen, M Ghassemi arXiv preprint arXiv:2009.08348, 2020	3	2020
Visual Similarity and Representation Learning T Milbich	1	2021

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