2D Instance Editing in 3D Space
Journal:
arXiv
Published Date:
Jul 8, 2025
Abstract
Generative models have achieved significant progress in advancing 2D image
editing, demonstrating exceptional precision and realism. However, they often
struggle with consistency and object identity preservation due to their
inherent pixel-manipulation nature. To address this limitation, we introduce a
novel "2D-3D-2D" framework. Our approach begins by lifting 2D objects into 3D
representation, enabling edits within a physically plausible,
rigidity-constrained 3D environment. The edited 3D objects are then reprojected
and seamlessly inpainted back into the original 2D image. In contrast to
existing 2D editing methods, such as DragGAN and DragDiffusion, our method
directly manipulates objects in a 3D environment. Extensive experiments
highlight that our framework surpasses previous methods in general performance,
delivering highly consistent edits while robustly preserving object identity.
