# TouchéWorld tech report : Towards Online Unified Camera--Hand Exploration in Generative Worlds

**Authors:** Jiaao Yu, Yanjian Zhang, Haoyang Jiang, Guillaume Wisniewski, Nadi Tomeh, Shijie Jia  
**Lab:** Centre National de la Recherche Scientifique · **Published:** 4 Nov 2026  
**Links:** [arXiv](https://arxiv.org/abs/2611.06061) · [PDF](https://arxiv.org/pdf/2611.06061) · [This page](https://omen-bit.github.io/ai-paper-daily/paper/2611.06061.html)

## Abstract

Recent video world models allow users to explore generated environments through camera navigation. Continuous hand motion provides a fine-grained action channel for interacting with the people and objects encountered during exploration. We present TouchéWorld, a framework that integrates gesture-driven interaction into a camera-controlled video world model. Given an initial image and a scene-description prompt, the model generates video conditioned on temporally aligned camera and hand controls. We construct joint camera--hand training data from heterogeneous egocentric videos through annotation completion, consistency-based filtering, and temporal alignment. Building on a pretrained camera-controlled world model, we combine spatial hand-skeleton conditioning with numerical hand-motion features through parameter-efficient adaptation. Causal adaptation and few-step distillation support chunk-level online generation, allowing users to update their controls based on generated visual feedback. We further introduce TouchéBench to evaluate hand-motion following, camera--hand coordination, online interaction, and object response. Together, these components establish a framework for studying continuous exploration and hand-driven interaction within generative worlds.

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