Advancements in Deep Learning for Pose Tracking in Computer Vision

The chapter explores the use of deep learning in pose tracking, specifically focusing on advancements in computer vision for studying animal behavior. It discusses the adaptation of human domain deep learning methods for scientific applications, emphasizing sample efficiency in training neural networks and reducing the need for extensive data labeling. The chapter also introduces a revolutionary method for quickly training neural networks with minimal annotations and highlights the development of the SLEEP project, an advanced framework for animal pose estimation.