In-N-Out: Faithful 3D GAN Inversion with Volumetric Decomposition for Face Editing

Understand

3D-aware GANs offer new capabilities for view synthesis while preserving the editing functionalities of their 2D counterparts.

• GAN inversion is a crucial step that seeks the latent code to reconstruct input images or videos, subsequently enabling diverse editing tasks through manipulation of this latent code.
• However, a model pre-trained on a particular dataset (e.g., FFHQ) often has difficulty reconstructing images with out-of-distribution (OOD) objects such as faces with heavy make-up or occluding objects.
• We address this issue by explicitly modeling OOD objects from the input in 3D-aware GANs.