AI RESEARCH
Exploring the Role of Synthetic Data Augmentation in Controllable Human-Centric Video Generation
arXiv CS.CV
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ArXi:2604.21291v1 Announce Type: new Controllable human video generation aims to produce realistic videos of humans with explicitly guided motions and appearances,serving as a foundation for digital humans, animation, and embodied AI. However, the scarcity of largescale, diverse, and privacy safe human video datasets poses a major bottleneck, especially for rare identities and complex actions. Synthetic data provides a scalable and controllable alternative,yet its actual contribution to generative modeling remains underexplored due to the persistent Sim2Real gap.