Search Results for author: Karsten Roth

Found 14 papers, 11 papers with code

Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning

1 code implementation20 Jul 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.

Metric Learning

Towards Total Recall in Industrial Anomaly Detection

4 code implementations15 Jun 2021 Karsten Roth, Latha Pemula, Joaquin Zepeda, Bernhard Schölkopf, Thomas Brox, Peter Gehler

Being able to spot defective parts is a critical component in large-scale industrial manufacturing.

 Ranked #1 on Anomaly Detection on MVTec AD (using extra training data)

Anomaly Detection Outlier Detection

S2SD: Simultaneous Similarity-based Self-Distillation for Deep Metric Learning

1 code implementation17 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.

Knowledge Distillation Metric Learning

Uniform Priors for Data-Efficient Transfer

no code implementations30 Jun 2020 Samarth Sinha, Karsten Roth, Anirudh Goyal, Marzyeh Ghassemi, Hugo Larochelle, Animesh Garg

Deep Neural Networks have shown great promise on a variety of downstream applications; but their ability to adapt and generalize to new data and tasks remains a challenge.

Domain Adaptation Meta-Learning +1

COVID-19 Image Data Collection: Prospective Predictions Are the Future

5 code implementations22 Jun 2020 Joseph Paul Cohen, Paul Morrison, Lan Dao, Karsten Roth, Tim Q Duong, Marzyeh Ghassemi

This dataset currently contains hundreds of frontal view X-rays and is the largest public resource for COVID-19 image and prognostic data, making it a necessary resource to develop and evaluate tools to aid in the treatment of COVID-19.

Sharing Matters for Generalization in Deep Metric Learning

no code implementations12 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.

Metric Learning

PADS: Policy-Adapted Sampling for Visual Similarity Learning

1 code implementation CVPR 2020 Karsten Roth, Timo Milbich, Björn Ommer

Learning visual similarity requires to learn relations, typically between triplets of images.

Revisiting Training Strategies and Generalization Performance in Deep Metric Learning

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.

Metric Learning

MIC: Mining Interclass Characteristics for Improved Metric Learning

2 code implementations ICCV 2019 Karsten Roth, Biagio Brattoli, Björn Ommer

In contrast, we propose to explicitly learn the latent characteristics that are shared by and go across object classes.

Image Retrieval Metric Learning

Mask Mining for Improved Liver Lesion Segmentation

no code implementations14 Aug 2019 Karsten Roth, Jürgen Hesser, Tomasz Konopczyński

We propose a novel procedure to improve liver and lesion segmentation from CT scans for U-Net based models.

Lesion Segmentation Tumor Segmentation

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