367 citations · 1k across the 6 of their papers we have counts for
5 papers · 1 filter
SuperAnimal pretrained pose estimation models for behavioral analysis
Shaokai Ye, Anastasiia Filippova, Jessy Lauer +5
Quantification of behavior is critical in applications ranging from neuroscience, veterinary medicine and animal conservation efforts. A common key step for behavioral analysis is…
Unsupervised Object Learning via Common Fate
Matthias Tangemann, Steffen Schneider, Julius von Kügelgen +6
Learning generative object models from unlabelled videos is a long standing problem and required for causal scene modeling. We decompose this problem into three easier subtasks, an…
A Primer on Motion Capture with Deep Learning: Principles, Pitfalls and Perspectives
Alexander Mathis, Steffen Schneider, Jessy Lauer +1
Extracting behavioral measurements non-invasively from video is stymied by the fact that it is a hard computational problem. Recent advances in deep learning have tremendously adva…
Pretraining boosts out-of-domain robustness for pose estimation
Alexander Mathis, Thomas Biasi, Steffen Schneider +4
Neural networks are highly effective tools for pose estimation. However, as in other computer vision tasks, robustness to out-of-domain data remains a challenge, especially for sma…
Context-based Normalization of Histological Stains using Deep Convolutional Features
Daniel Bug, Steffen Schneider, Anne Grote +4
While human observers are able to cope with variations in color and appearance of histological stains, digital pathology algorithms commonly require a well-normalized setting to ac…