Generated Reality: Human-centric World Simulation using Interactive Video Generation with Hand and Camera Control

The paper introduces a human‑centric video world model that can be controlled by tracked head pose and joint‑level hand poses, enabling realistic hand‑object interactions. It evaluates existing diffusion transformer conditioning methods and proposes a new 3‑D control mechanism, training a bidirectional diffusion model and distilling it into a causal, interactive system for egocentric virtual environments. Human‑subject experiments show that the system improves task performance and gives users a higher perceived sense of control compared to baseline methods.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

• llms
• diffusion
• robotics