A Dataset of Relighted 3D Interacting Hands
Gyeongsik Moon Shunsuke Saito Weipeng Xu Rohan Joshi Julia Buffalini Harley Bellan Nicholas Rosen Jesse Richardson Mallorie Mize Philippe de Bree Tomas Simon Bo Peng Shubham Garg Kevyn McPhail Takaaki Shiratori
The two-hand interaction is one of the most challenging signals to analyze
due to the self-similarity, complicated articulations, and occlusions of hands.
Although several datasets have been proposed for the two-hand interaction
analysis, all of them do not achieve 1) diverse and realistic image appearances
and 2) diverse and large-scale groundtruth (GT) 3D poses at the same time. In
this work, we propose Re:InterHand, a dataset of relighted 3D interacting hands
that achieve the two goals. To this end, we employ a state-of-the-art hand
relighting network with our accurately tracked two-hand 3D poses. We compare
our Re:InterHand with existing 3D interacting hands datasets and show the
benefit of it. Our Re:InterHand is available in
https://mks0601.github.io/ReInterHand/.