collaborators

12 papers

cs.CV2026

Muses: Designing, Composing, Generating Nonexistent Fantasy 3D Creatures without Training

Hexiao Lu, Xiaokun Sun, Zeyu Cai +4

We present Muses, the first training-free method for fantastic 3D creature generation in a feed-forward paradigm. Previous methods, which rely on part-aware optimization, manual as…

cs.CV2026

ETCH-X: Robustify Expressive Body Fitting to Clothed Humans with Composable Datasets

Xiaoben Li, Jingyi Wu, Zeyu Cai +3

Human body fitting, which aligns parametric body models such as SMPL to raw 3D point clouds of clothed humans, serves as a crucial first step for downstream tasks like animation an…

cs.CV2026

OmniFit: Multi-modal 3D Body Fitting via Scale-agnostic Dense Landmark Prediction

Zeyu Cai, Yuliang Xiu, Renke Wang +8

Fitting an underlying body model to 3D clothed human assets has been extensively studied, yet most approaches focus on either single-modal inputs such as point clouds or multi-view…

cs.CV2026

GaussiAnimate: Reconstruct and Rig Animatable Categories with Level of Dynamics

Jiaxin Wang, Dongxin Lyu, Zeyu Cai +4

Free-form bones, that conform closely to the surface, can effectively capture non-rigid deformations, but lack a kinematic structure necessary for intuitive control. Thus, we propo…

cs.CV2026

UP2You: Fast Reconstruction of Yourself from Unconstrained Photo Collections

Zeyu Cai, Ziyang Li, Xiaoben Li +4

We present UP2You, the first tuning-free solution for reconstructing high-fidelity 3D clothed portraits from extremely unconstrained in-the-wild 2D photos. Unlike previous approach…

cs.CV2026

MorphAny3D: Unleashing the Power of Structured Latent in 3D Morphing

Xiaokun Sun, Zeyu Cai, Hao Tang +3

3D morphing remains challenging due to the difficulty of generating semantically consistent and temporally smooth deformations, especially across categories. We present MorphAny3D,…