4 accepted papers
Analyzing human posture and precisely comparing it across different subjects is essential for accurate understanding of behavior and numerous vision applications such as medical diagnostics, sports, or surveillance. Motion magnification techniques help to see even small deviations in posture that ar…
Learning the embedding space, where semantically similar objects are located close together and dissimilar objects far apart, is a cornerstone of many computer vision applications. Existing approaches usually learn a single metric in the embedding space for all available data points, which may hav…
Self-supervised learning of convolutional neural networks can harness large amounts of cheap unlabeled data to train powerful feature representations. As surrogate task, we jointly address ordering of visual data in the spatial and temporal domain. The permutations of training samples, which are at…
Behavior analysis provides a crucial non-invasive and easily accessible diagnostic tool for biomedical research. A detailed analysis of posture changes during skilled motor tasks can reveal distinct functional deficits and their restoration during recovery. Our specific scenario is based on a neuros…