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NeurIPS2024Top-tier venue

ReplaceAnything3D: Text-Guided Object Replacement in 3D Scenes with Compositional Scene Representations

Edward Bartrum, Thu Nguyen-Phuoc, Christopher Xie, Zhengqin Li, Numair Khan, Armen Avetisyan, Douglas Lanman, Lei Xiao

2024Year
5Citations
2Top-tier citations

Abstract

We introduce ReplaceAnything3D model (RAM3D), a novel method for 3D object replacement in 3D scenes based on users’ text description. Given multi-view images of a scene, a text prompt describing the object to replace, and another describing the new object, our Erase-and-Replace approach can effectively swap objects in 3D scenes with newly generated content while maintaining 3D consistency across multiple viewpoints. We demonstrate the versatility of RAM3D by applying it to various realistic 3D scene types, showcasing results of modified objects that blend in seamlessly with the scene without impacting its overall integrity.

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