3D-Adapter: Geometry-Consistent Multi-View Diffusion for High-Quality 3D Generation
On the map: Diffusion models → 3D, point cloud and scene generation
Abstract (arXiv)
Multi-view image diffusion models have significantly advanced open-domain 3D object generation. However, most existing models rely on 2D network architectures that lack inherent 3D biases, resulting in compromised geometric consistency. To address this challenge, we introduce 3D-Adapter, a plug-in module designed to infuse 3D geometry awareness into pretrained image diffusion models. Central to our approach is the idea of 3D feedback augmentation: for each denoising step in the sampling loop, 3D-Adapter decodes intermediate multi-view features into a coherent 3D representation, then re-encodes the rendered RGBD views to augment the pretrained base model through feature addition. We study two variants of 3D-Adapter: a fast feed-forward version based on Gaussian splatting and a versatile training-free version utilizing neural fields and meshes. Our extensive experiments demonstrate that 3D-Adapter not only greatly enhances the geometry quality of text-to-multi-view models such as Instant3D and Zero123++, but also enables high-quality 3D generation using the plain text-to-image Stable Diffusion. Furthermore, we showcase the broad application potential of 3D-Adapter by presenting high quality results in text-to-3D, image-to-3D, text-to-texture, and text-to-avatar tasks.
Key facts. Cited by 19 papers in the map (data through 14 Oct 2026). Placed in 3D, point cloud and scene generation, one of 14 directions in Diffusion models. Builds on 85 of its 94 references that are in the map. First posted on arXiv 24 Oct 2024.
Builds on
85 of 94 references.
Closest ancestors · 28
Same direction, newest first
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Other references · 57
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- 20218-bit Optimizers via Block-wise Quantizationcited by 403
- 2024GRM: Large Gaussian Reconstruction Model for Efficient 3D Reconstruction and Generationcited by 301
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- 2024Classifier-Free Guidance is a Predictor-Correctorcited by 84
- 2023Free3D: Consistent Novel View Synthesis without 3D Representationcited by 72
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