TextMesh4D: High-Quality Text-to-4D Mesh Generation

• URL: http://arxiv.org/abs/2506.24121v1
• Date: Mon, 30 Jun 2025 17:58:34 GMT
• Title: TextMesh4D: High-Quality Text-to-4D Mesh Generation
• Authors: Sisi Dai, Xinxin Su, Boyan Wan, Ruizhen Hu, Kai Xu,
• Abstract summary: We introduce TextMesh4D, a novel framework for high-quality text-to-4D generation.<n>Our approach leverages per-face Jacobians as a differentiable mesh representation and decomposes 4D generation into two stages: static object creation and dynamic motion synthesis.<n> Experiments demonstrate that TextMesh4D state-of-the-art results in terms of temporal consistency, structural fidelity, and visual realism.
• Score: 13.069414103080447
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Recent advancements in diffusion generative models significantly advanced image, video, and 3D content creation from user-provided text prompts. However, the challenging problem of dynamic 3D content generation (text-to-4D) with diffusion guidance remains largely unexplored. In this paper, we introduce TextMesh4D, a novel framework for high-quality text-to-4D generation. Our approach leverages per-face Jacobians as a differentiable mesh representation and decomposes 4D generation into two stages: static object creation and dynamic motion synthesis. We further propose a flexibility-rigidity regularization term to stabilize Jacobian optimization under video diffusion priors, ensuring robust geometric performance. Experiments demonstrate that TextMesh4D achieves state-of-the-art results in terms of temporal consistency, structural fidelity, and visual realism. Moreover, TextMesh4D operates with a low GPU memory overhead-requiring only a single 24GB GPU-offering a cost-effective yet high-quality solution for text-driven 4D mesh generation. The code will be released to facilitate future research in text-to-4D generation.

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