Animate Any Character in Any World

• URL: http://arxiv.org/abs/2512.17796v1
• Date: Thu, 18 Dec 2025 18:59:18 GMT
• Title: Animate Any Character in Any World
• Authors: Yitong Wang, Fangyun Wei, Hongyang Zhang, Bo Dai, Yan Lu,
• Abstract summary: We introduce AniX, leveraging the realism and structural grounding of static world generation.<n>Users can provide a 3DGS scene and a character, then direct the character through natural language to perform diverse behaviors.<n>AiX synthesizes temporally coherent video clips that preserve visual fidelity with the provided scene and character.
• Score: 61.112404900403284
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Recent advances in world models have greatly enhanced interactive environment simulation. Existing methods mainly fall into two categories: (1) static world generation models, which construct 3D environments without active agents, and (2) controllable-entity models, which allow a single entity to perform limited actions in an otherwise uncontrollable environment. In this work, we introduce AniX, leveraging the realism and structural grounding of static world generation while extending controllable-entity models to support user-specified characters capable of performing open-ended actions. Users can provide a 3DGS scene and a character, then direct the character through natural language to perform diverse behaviors from basic locomotion to object-centric interactions while freely exploring the environment. AniX synthesizes temporally coherent video clips that preserve visual fidelity with the provided scene and character, formulated as a conditional autoregressive video generation problem. Built upon a pre-trained video generator, our training strategy significantly enhances motion dynamics while maintaining generalization across actions and characters. Our evaluation covers a broad range of aspects, including visual quality, character consistency, action controllability, and long-horizon coherence.

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