A Method for Detecting Interaction between 3D Hands and Unknown Objects in RGB Video. Issue 1 (April 2021) - Wu, Yankun; Wang, Peipei; Wang, Xin; Liu, Guanqun; Zhao, Lin; Xiang, Ji
Abstract: We propose a model that can extract 3D position of hand and object in per-frame of RGB videos through a single feed-forward neural network and a zero-shot learning classifier, and understand unknown hand-object interactions in the entire video through an interactive temporal module. The process is trained end-to-end, without depth images or annotated coordinates as input, which has good application prospects in real life.