Self-Supervised 4D Point Cloud Feature Learning for Activity Recognition
Master Practical Training Project Status: available Supervisors: Irene Ballester, Martin Kampel Problem Statement This project aims to address the challenges associated with the expensive and time-consuming annotation of 3D data by exploring a self-supervised approach for the extraction of 4D spatio-temporal features from dynamic point cloud data. Specifically, the project investigates the prediction of the temporal … Continue reading Self-Supervised 4D Point Cloud Feature Learning for Activity Recognition