8 code implementations • ICML 2020 • Karsten Roth, Timo Milbich, Samarth Sinha, Prateek Gupta, Björn Ommer, Joseph Paul Cohen
Deep Metric Learning (DML) is arguably one of the most influential lines of research for learning visual similarities with many proposed approaches every year.
1 code implementation • CVPR 2021 • Michael Dorkenwald, Timo Milbich, Andreas Blattmann, Robin Rombach, Konstantinos G. Derpanis, Björn Ommer
Video understanding calls for a model to learn the characteristic interplay between static scene content and its dynamics: Given an image, the model must be able to predict a future progression of the portrayed scene and, conversely, a video should be explained in terms of its static image content and all the remaining characteristics not present in the initial frame.
1 code implementation • CVPR 2020 • Karsten Roth, Timo Milbich, Björn Ommer
Learning visual similarity requires to learn relations, typically between triplets of images.
Ranked #17 on Metric Learning on CUB-200-2011 (using extra training data)
1 code implementation • CVPR 2021 • Andreas Blattmann, Timo Milbich, Michael Dorkenwald, Björn Ommer
Given a static image of an object and a local poking of a pixel, the approach then predicts how the object would deform over time.
2 code implementations • ICCV 2021 • Andreas Blattmann, Timo Milbich, Michael Dorkenwald, Björn Ommer
There will be distinctive movement, despite evident variations caused by the stochastic nature of our world.
2 code implementations • CVPR 2019 • Dominik Lorenz, Leonard Bereska, Timo Milbich, Björn Ommer
Large intra-class variation is the result of changes in multiple object characteristics.
Ranked #3 on Unsupervised Human Pose Estimation on Human3.6M
1 code implementation • 17 Sep 2020 • Karsten Roth, Timo Milbich, Björn Ommer, Joseph Paul Cohen, Marzyeh Ghassemi
Deep Metric Learning (DML) provides a crucial tool for visual similarity and zero-shot applications by learning generalizing embedding spaces, although recent work in DML has shown strong performance saturation across training objectives.
Ranked #10 on Metric Learning on CARS196 (using extra training data)
2 code implementations • ECCV 2020 • Timo Milbich, Karsten Roth, Homanga Bharadhwaj, Samarth Sinha, Yoshua Bengio, Björn Ommer, Joseph Paul Cohen
Visual Similarity plays an important role in many computer vision applications.
Ranked #13 on Metric Learning on CUB-200-2011 (using extra training data)
1 code implementation • CVPR 2021 • Andreas Blattmann, Timo Milbich, Michael Dorkenwald, Björn Ommer
Using this representation, we are able to change the behavior of a person depicted in an arbitrary posture, or to even directly transfer behavior observed in a given video sequence.
2 code implementations • NeurIPS 2021 • Timo Milbich, Karsten Roth, Samarth Sinha, Ludwig Schmidt, Marzyeh Ghassemi, Björn Ommer
Finally, we propose few-shot DML as an efficient way to consistently improve generalization in response to unknown test shifts presented in ooDML.
no code implementations • ICCV 2017 • Timo Milbich, Miguel Bautista, Ekaterina Sutter, Bjorn Ommer
Without any manual annotation, the model learns a structured representation of postures and their temporal development.
no code implementations • 18 Nov 2019 • Timo Milbich, Omair Ghori, Ferran Diego, Björn Ommer
To nevertheless find those relations which can be reliably utilized for learning, we follow a divide-and-conquer strategy: We find reliable similarities by extracting compact groups of images and reliable dissimilarities by partitioning these groups into subsets, converting the complicated overall problem into few reliable local subproblems.
no code implementations • 12 Apr 2020 • Timo Milbich, Karsten Roth, Biagio Brattoli, Björn Ommer
The common paradigm is discriminative metric learning, which seeks an embedding that separates different training classes.
no code implementations • CVPR 2023 • Dmytro Kotovenko, Pingchuan Ma, Timo Milbich, Björn Ommer
Experiments on established DML benchmarks show that our cross-attention conditional embedding during training improves the underlying standard DML pipeline significantly so that it outperforms the state-of-the-art.
no code implementations • 8 Jan 2024 • Jonas Dippel, Barbara Feulner, Tobias Winterhoff, Simon Schallenberg, Gabriel Dernbach, Andreas Kunft, Stephan Tietz, Timo Milbich, Simon Heinke, Marie-Lisa Eich, Julika Ribbat-Idel, Rosemarie Krupar, Philipp Jurmeister, David Horst, Lukas Ruff, Klaus-Robert Müller, Frederick Klauschen, Maximilian Alber
Histopathology plays a central role in clinical medicine and biomedical research.