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ReplaceAnything3D:Text-Guided 3D Scene Editing with Compositional Neural Radiance Fields

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arxiv 2401.17895 v1 pith:SOYBB3TO submitted 2024-01-31 cs.CV cs.AIcs.GR

Edward Bartrum , Thu Nguyen-Phuoc , Chris Xie , Zhengqin Li , Numair Khan , Armen Avetisyan , Douglas Lanman , Lei Xiao This is my paper
classification cs.CVcs.AIcs.GR
keywords sceneobjectsreplaceanything3ddescribingeditingobjectprompttext
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We introduce ReplaceAnything3D model (RAM3D), a novel text-guided 3D scene editing method that enables the replacement of specific objects within a scene. Given multi-view images of a scene, a text prompt describing the object to replace, and a text prompt describing the new object, our Erase-and-Replace approach can effectively swap objects in the scene with newly generated content while maintaining 3D consistency across multiple viewpoints. We demonstrate the versatility of ReplaceAnything3D by applying it to various realistic 3D scenes, showcasing results of modified foreground objects that are well-integrated with the rest of the scene without affecting its overall integrity.

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Cited by 1 Pith paper

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

  1. DiGA3D: Coarse-to-Fine Diffusional Propagation of Geometry and Appearance for Versatile 3D Inpainting

    cs.CV 2025-07 conditional novelty 5.0 of 10

    DiGA3D performs text-guided 3D inpainting (removal, re-texturing, replacement) with a coarse-to-fine diffusion propagation scheme to improve multi-view appearance and geometry consistency.

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