Instant3dit: Multiview Inpainting for Fast Editing of 3D Objects

Amir Barda, Matheus Gadelha, Vladimir G. Kim, Noam Aigerman, Amit Bermano +1 more
2/9/2026

No official code found. Best implementation: amirbarda/Instant3dit (68 stars, last commit 2025-08-05).

Abstract

We propose a generative technique to edit 3D shapes, represented as meshes, NeRFs, or Gaussian Splats, in ≈ 3 seconds, without the need for running an SDS type of optimization. Our key insight is to cast 3D editing as a multiview image inpainting problem, as this representation is generic and can be mapped back to any 3D representation using the bank of available Large Reconstruction Models. We explore different fine-tuning strategies to obtain both multiview generation and inpainting capabilities within the same diffusion model. In particular, the design of the inpainting mask is an important factor of training an inpainting model, and we propose several masking strategies to mimic the types of edits a user would perform on a 3D shape. Our approach takes 3D generative editing from hours to seconds and produces higher-quality results compared to previous works.

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Code Implementations(1)

Instant3dit: Multiview Inpainting for Fast Editing of 3D Objects (CVPR 2025)

683Shell, PythonNov 30, 20241 years agoNOASSERTION

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Cite this paper

@article{barda2026instantdit,
  title  = {Instant3dit: Multiview Inpainting for Fast Editing of 3D Objects},
  author = {Amir Barda and Matheus Gadelha and Vladimir G. Kim and Noam Aigerman and Amit Bermano and Thibault Groueix},
  year   = {2026},
  eprint = {2412.00518},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/abs/2412.00518},
  journal = {CVPR 2024 2024}
}

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