22 citations · 22 across the 5 of their papers we have counts for
6 papers
Nexus: Native Mesh Generation with Diffusion
Hanxiao Wang, Ying-Tian Liu, Yuan-Chen Guo +5
Generating high-quality triangle meshes is essential for film, gaming, and interactive 3D applications. Mainstream methods rely on mesh serialization and autoregressive processes,…
SeamGen: Artist-Aligned UV Seam Generation via Graph Flow Matching
Hao Xu, Yuqing Zhang, Yiqian Wu +5
UV seam placement is a critical yet labor-intensive step in 3D content creation, requiring artists to balance chart shape, seam concealment, and alignment with semantic and geometr…
FACE: A Face-based Autoregressive Representation for High-Fidelity and Efficient Mesh Generation
Hanxiao Wang, Yuan-Chen Guo, Ying-Tian Liu +6
Autoregressive models for 3D mesh generation suffer from a fundamental limitation: they flatten meshes into long vertex-coordinate sequences. This results in prohibitive computatio…
OmniPart: Part-Aware 3D Generation with Semantic Decoupling and Structural Cohesion
Yunhan Yang, Yufan Zhou, Yuan-Chen Guo +7
The creation of 3D assets with explicit, editable part structures is crucial for advancing interactive applications, yet most generative methods produce only monolithic shapes, lim…
TEXGen: a Generative Diffusion Model for Mesh Textures
Xin Yu, Ze Yuan, Yuan-Chen Guo +6
While high-quality texture maps are essential for realistic 3D asset rendering, few studies have explored learning directly in the texture space, especially on large-scale datasets…
Learning Implicit Glyph Shape Representation
Ying-Tian Liu, Yuan-Chen Guo, Yi-Xiao Li +2
In this paper, we present a novel implicit glyph shape representation, which models glyphs as shape primitives enclosed by quadratic curves, and naturally enables generating glyph…