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

arXiv: https://arxiv.org/abs/2602.18422 · HTML: https://mlsanity.com/paper/2602.18422/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- Placed in Embodied and robot world models, one of 11 directions in World models.
- Builds on 2 of its 45 references that are in the map.
- First posted on arXiv 20 Feb 2026.

## Placed in

- World models / [Embodied and robot world models](https://mlsanity.com/wm/embodied-and-robot-world-models/)
- Diffusion models / [Diffusion and flow policies for robotics](https://mlsanity.com/diffusion/diffusion-and-flow-policies-for-robotics/)

## Builds on (most cited first, 2 of 2)

- [Wan: Open and Advanced Large-Scale Video Generative Models](https://mlsanity.com/paper/2503.20314/) (2025)
- [Context as Memory: Scene-Consistent Interactive Long Video Generation with Memory Retrieval](https://mlsanity.com/paper/2506.03141/) (2025)

## Built on by (most cited first, 13 of 13)

- [LOME: Learning Human-Object Manipulation with Action-Conditioned Egocentric World Model](https://mlsanity.com/paper/2603.27449/) (2026)
- [Egocentric World Model for Photorealistic Hand-Object Interaction Synthesis](https://mlsanity.com/paper/2603.13615/) (2026)
- [Masked Visual Actions for Unified World Modeling](https://mlsanity.com/paper/2607.19343/) (2026)
- [Worldscape-MoE: A Unified Mixture-of-Experts World Model for Scalable Heterogeneous Action Control](https://mlsanity.com/paper/2607.03964/) (2026)
- [Pyramid Forcing: Head-Aware Pyramid KV Cache Policy for High-Quality Long Video Generation](https://mlsanity.com/paper/2605.13111/) (2026)
- [AnchorWorld: Embodied Egocentric World Simulation with View-based Evolution Customization](https://mlsanity.com/paper/2606.07326/) (2026)
- [RynnWorld-Teleop: An Action-Conditioned World Model for Digital Teleoperation](https://mlsanity.com/paper/2607.06558/) (2026)
- [HandsOnWorld: Unconstrained Egocentric Video Generation with Camera-Disentangled Hand Control](https://mlsanity.com/paper/2607.02075/) (2026)
- [EgoPlay: Event-Triggered Video Editing for Egocentric Streams](https://mlsanity.com/paper/2607.24560/) (2026)
- [Hand-Object Interaction in the Age of Large Foundation Models:Reconstruction, Generation, and Embodied Transfer](https://mlsanity.com/paper/2607.28394/) (2026)
- [Human-Centric Intelligence in the Era of Foundation Models: A Survey](https://mlsanity.com/paper/2608.18184/) (2026)
- [Code Plans, Diffusion Renders: Open-Ended Generative World Modeling](https://mlsanity.com/paper/2609.26458/) (2026)
- [Multi-Agent Egocentric World Model with Fine-Grained Embodied Interaction](https://mlsanity.com/paper/2610.12299/) (2026)

## Abstract (arXiv)

Extended reality (XR) demands generative models that respond to users' tracked real-world motion, yet current video world models accept only coarse control signals such as text or keyboard input, limiting their utility for embodied interaction. We introduce a human-centric video world model that is conditioned on both tracked head pose and joint-level hand poses. For this purpose, we evaluate existing diffusion transformer conditioning strategies and propose an effective mechanism for 3D head and hand control, enabling dexterous hand--object interactions. We train a bidirectional video diffusion model teacher using this strategy and distill it into a causal, interactive system that generates egocentric virtual environments. We evaluate this generated reality system with human subjects and demonstrate improved task performance as well as a significantly higher level of perceived amount of control over the performed actions compared with relevant baselines.