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From the 2 of 5 linked papers with an AI index.

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20242026
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5 papers

cs.CV2026

Nexus: Native Mesh Generation with Diffusion

Hanxiao Wang, Ying-Tian Liu, Yuan-Chen Guo +5

The paper introduces Nexus, a diffusion-based approach that generates high-quality triangle meshes by separately modeling vertex positions with an octree-based diffusion process an…

cs.CV2026

SeamGen: Artist-Aligned UV Seam Generation via Graph Flow Matching

Hao Xu, Yuqing Zhang, Yiqian Wu +5

The paper introduces SeamGen, a generative model that learns artist-preferred UV seam layouts from existing data using flow‑matching and a mesh‑aware Transformer, enabling controll…

cs.CV2026

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…

cs.CV2025

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…

cs.CV2024

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…