ReGenNet introduces a novel approach to human action-reaction synthesis, focusing on asymmetric, dynamic, synchronous, and detailed interactions. The model generates instant and plausible human reactions conditioned on given actions. By annotating actor-reactor orders in datasets like NTU120, Chi3D, and InterHuman, ReGenNet achieves state-of-the-art results in FID scores, action recognition accuracy, diversity, and multi-modality. The model is modular and flexible for various settings of conditional action-reaction generation.
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