22 citations · 32 across the 11 of their papers we have counts for
11 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…
3D Gaussian Editing with A Single Image
Guan Luo, Tian-Xing Xu, Ying-Tian Liu +3
The modeling and manipulation of 3D scenes captured from the real world are pivotal in various applications, attracting growing research interest. While previous works on editing h…
PPEA-Depth: Progressive Parameter-Efficient Adaptation for Self-Supervised Monocular Depth Estimation
Yue-Jiang Dong, Yuan-Chen Guo, Ying-Tian Liu +2
Self-supervised monocular depth estimation is of significant importance with applications spanning across autonomous driving and robotics. However, the reliance on self-supervision…
PI3D: Efficient Text-to-3D Generation with Pseudo-Image Diffusion
Ying-Tian Liu, Yuan-Chen Guo, Guan Luo +3
Diffusion models trained on large-scale text-image datasets have demonstrated a strong capability of controllable high-quality image generation from arbitrary text prompts. However…
DualVector: Unsupervised Vector Font Synthesis with Dual-Part Representation
Ying-Tian Liu, Zhifei Zhang, Yuan-Chen Guo +3
Automatic generation of fonts can be an important aid to typeface design. Many current approaches regard glyphs as pixelated images, which present artifacts when scaling and inevit…
Enhancing Multi-Scale Implicit Learning in Image Super-Resolution with Integrated Positional Encoding
Ying-Tian Liu, Yuan-Chen Guo, Song-Hai Zhang
Is the center position fully capable of representing a pixel? There is nothing wrong to represent pixels with their centers in a discrete image representation, but it makes more se…
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…