MvDrag3D: Drag-based Creative 3D Editing via Multi-view Generation-Reconstruction Priors

• URL: http://arxiv.org/abs/2410.16272v1
• Date: Mon, 21 Oct 2024 17:59:53 GMT
• Title: MvDrag3D: Drag-based Creative 3D Editing via Multi-view Generation-Reconstruction Priors
• Authors: Honghua Chen, Yushi Lan, Yongwei Chen, Yifan Zhou, Xingang Pan,
• Abstract summary: Existing 3D drag-based editing methods fall short in handling significant topology changes or generating new textures across diverse object categories. We introduce MVDrag3D, a novel framework for more flexible and creative drag-based 3D editing. We show that MVDrag3D provides a precise, generative, and flexible solution for 3D drag-based editing.
• Score: 19.950368071777092
• License:
• Abstract: Drag-based editing has become popular in 2D content creation, driven by the capabilities of image generative models. However, extending this technique to 3D remains a challenge. Existing 3D drag-based editing methods, whether employing explicit spatial transformations or relying on implicit latent optimization within limited-capacity 3D generative models, fall short in handling significant topology changes or generating new textures across diverse object categories. To overcome these limitations, we introduce MVDrag3D, a novel framework for more flexible and creative drag-based 3D editing that leverages multi-view generation and reconstruction priors. At the core of our approach is the usage of a multi-view diffusion model as a strong generative prior to perform consistent drag editing over multiple rendered views, which is followed by a reconstruction model that reconstructs 3D Gaussians of the edited object. While the initial 3D Gaussians may suffer from misalignment between different views, we address this via view-specific deformation networks that adjust the position of Gaussians to be well aligned. In addition, we propose a multi-view score function that distills generative priors from multiple views to further enhance the view consistency and visual quality. Extensive experiments demonstrate that MVDrag3D provides a precise, generative, and flexible solution for 3D drag-based editing, supporting more versatile editing effects across various object categories and 3D representations.

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