a few-shot learning framework for multi-animal 3D pose estimation, identity recognition and social behaviour classification. We propose a continuous occlusion copy-and-paste algorithm (COCA) for data augmentation in SBeA, combined with a multiview camera, to achieve multi-animal 3D social pose esti...
Here we show a computational framework, the Social Behavior Atlas (SBeA) used to overcome the problem caused by the limited datasets. SBeA uses a much smaller number of labelled frames for multi-animal three-dimensional pose estimation, achieves label-free identification recognition and successfully...
In the code, we provide 3D support for multi-animal pose estimation (via multi-camera use), plus this multi-animal variant can be integrated with our real-time software, DeepLabCut-Live!28. Another important user input is at the stage of tracking, where users can input how many animals ...
The desire to understand how the brain generates and patterns behavior has driven rapid methodological innovation in tools to quantify natural animal behavior. While advances in deep learning and computer vision have enabled markerless pose estimation in