4 papers
CANIS: Generation-Assisted 3D Canonicalization via an Image-Semantic Bridge
Kendong Liu, Yuxin Yao, Junhui Hou
Canonicalizing 3D object orientation is fundamental to 3D understanding and analysis. Existing approaches often rely on geometric cues, although 3D canonicalization ultimately requ…
G-Skin: Learning to Bind 3D Gaussians with Generative Visual Priors
Yuxin Yao, Kendong Liu, Shiqi Zhou +2
3D Gaussian Splatting has achieved remarkable success in photorealistic and efficient rendering, leading to a rapid increase in 3D assets represented by 3D Gaussian primitives. Dir…
GSwap: Realistic Head Swapping with Dynamic Neural Gaussian Field
Jingtao Zhou, Xuan Gao, Dongyu Liu +3
We present GSwap, a novel consistent and realistic video head-swapping system empowered by dynamic neural Gaussian portrait priors, which significantly advances the state of the ar…
RigGS: Rigging of 3D Gaussians for Modeling Articulated Objects in Videos
Yuxin Yao, Zhi Deng, Junhui Hou
This paper considers the problem of modeling articulated objects captured in 2D videos to enable novel view synthesis, while also being easily editable, drivable, and re-posable. T…