3D-GOI: 3D GAN Omni-Inversion for Multifaceted and Multi-object Editing
This addresses the need for more comprehensive editing tools in computer vision and graphics, particularly for applications like virtual reality and content creation, though it appears incremental as it builds on existing 3D GAN methods like GIRAFFE.
The paper tackles the problem of limited editing capabilities in GAN inversion methods by proposing 3D-GOI, a framework that enables multifaceted editing (scale, translation, rotation) on multiple objects in 3D scenes, achieving flexible editing in complex multi-object scenes as demonstrated by qualitative and quantitative experiments.
The current GAN inversion methods typically can only edit the appearance and shape of a single object and background while overlooking spatial information. In this work, we propose a 3D editing framework, 3D-GOI, to enable multifaceted editing of affine information (scale, translation, and rotation) on multiple objects. 3D-GOI realizes the complex editing function by inverting the abundance of attribute codes (object shape/appearance/scale/rotation/translation, background shape/appearance, and camera pose) controlled by GIRAFFE, a renowned 3D GAN. Accurately inverting all the codes is challenging, 3D-GOI solves this challenge following three main steps. First, we segment the objects and the background in a multi-object image. Second, we use a custom Neural Inversion Encoder to obtain coarse codes of each object. Finally, we use a round-robin optimization algorithm to get precise codes to reconstruct the image. To the best of our knowledge, 3D-GOI is the first framework to enable multifaceted editing on multiple objects. Both qualitative and quantitative experiments demonstrate that 3D-GOI holds immense potential for flexible, multifaceted editing in complex multi-object scenes.Our project and code are released at https://3d-goi.github.io .