Toward Reliable Human Pose Forecasting with Uncertainty

arXiv:2304.06707v2 Announce Type: replace
Abstract: Recently, there has been an arms race of pose forecasting methods aimed at solving the spatio-temporal task of predicting a sequence of future 3D poses of a person given a sequence of past observed ones. However, the lack of unified benchmarks and limited uncertainty analysis have hindered progress in the field. To address this, we first develop an open-source library for human pose forecasting, including multiple models, supporting several datasets, and employing standardized evaluation metrics, …

arxiv cs.cv cs.hc cs.ro forecasting human type uncertainty