Track, Inpaint, Resplat: Subject-driven 3D and 4D Generation with
  Progressive Texture Infilling
Authors: name: Shuhong Zheng, name: Ashkan Mirzaei, name: Igor Gilitschenski

Current 3D/4D generation methods are usually optimized for photorealism,
efficiency, and aesthetics. However, they often fail to preserve the semantic
identity of the subject across different viewpoints. Adapting generation
methods with one or few images of a specific subject (also known as
Personalization or Subject-driven generation) allows generating visual content
that align with the identity of the subject. However, personalized 3D/4D
generation is still largely underexplored. In this work, we introduce TIRE
(Track, Inpaint, REsplat), a novel method for subject-driven 3D/4D generation.
It takes an initial 3D asset produced by an existing 3D generative model as
input and uses video tracking to identify the regions that need to be modified.
Then, we adopt a subject-driven 2D inpainting model for progressively infilling
the identified regions. Finally, we resplat the modified 2D multi-view
observations back to 3D while still maintaining consistency. Extensive
experiments demonstrate that our approach significantly improves identity
preservation in 3D/4D generation compared to state-of-the-art methods. Our
project website is available at
https://zsh2000.github.io/track-inpaint-resplat.github.io/.