Geometry-Aware Retargeting for Two-Skinned Characters Interaction

Inseo Jang, Soojin Choi, Seokhyeon Hong, Chaelin Kim, Junyong Noh

Abstract: Interactive motion between multiple characters is widely utilized in games and movies. However, the method for generating interactive motions considering the character's diverse mesh shape has yet to be studied. We propose a Spatio Cooperative Transformer (SCT) to retarget the interacting motions of two characters having arbitrary mesh connectivity. SCT predicts the residual of root position and joint rotations considering the shape difference between the source and target of interacting characters. In addition, we introduce an anchor loss function for SCT to maintain the geometric distance between the interacting characters when they are retargeted. We also propose a motion augmentation method with deformation-based adaptation to prepare a source-target paired dataset with an identical mesh connectivity for training. In experiments, our method achieved higher accuracy for semantic preservation and produced less artifacts of inter-penetration between the interacting characters for unseen characters and motions than the baselines. Moreover, we conducted a user evaluation using characters with various shapes, spanning low-to-high interaction levels to prove better semantic preservation of our method compared to previous studies.