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arxiv: 2407.02599 · v1 · pith:4IP4S2JM · submitted 2024-07-02 · cs.CV · cs.AI· cs.GR· cs.LG

Meta 3D Gen

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classification cs.CV cs.AIcs.GRcs.LG
keywords dgenmetaassetspacefidelitygenerationpromptshapes
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We introduce Meta 3D Gen (3DGen), a new state-of-the-art, fast pipeline for text-to-3D asset generation. 3DGen offers 3D asset creation with high prompt fidelity and high-quality 3D shapes and textures in under a minute. It supports physically-based rendering (PBR), necessary for 3D asset relighting in real-world applications. Additionally, 3DGen supports generative retexturing of previously generated (or artist-created) 3D shapes using additional textual inputs provided by the user. 3DGen integrates key technical components, Meta 3D AssetGen and Meta 3D TextureGen, that we developed for text-to-3D and text-to-texture generation, respectively. By combining their strengths, 3DGen represents 3D objects simultaneously in three ways: in view space, in volumetric space, and in UV (or texture) space. The integration of these two techniques achieves a win rate of 68% with respect to the single-stage model. We compare 3DGen to numerous industry baselines, and show that it outperforms them in terms of prompt fidelity and visual quality for complex textual prompts, while being significantly faster.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Determinism of Randomness: Prompt-Residual Seed Shaping for Diffusion Generation

    cs.CV 2025-11 unverdicted novelty 7.0

    A geometric view of semantic anisotropy in diffusion latents motivates a prompt-residual seed-shaping method that improves prompt alignment and visual quality without training.

  2. A Cross-Model VLM-Judge Protocol for Single-Image 3D Mesh Quality (and Why Cheap Proxies Fall Short)

    cs.LG 2026-06 unverdicted novelty 6.0

    A reproducible VLM-judge protocol with position-bias correction is validated as superior to CLIP similarity and geometry-validity proxies for assessing single-image 3D mesh quality.