most citedTEXGen: a Generative Diffusion Model for Mesh Textures

22 citations · 25 across the 5 of their papers we have counts for

collaborators
Showing cs.CVShow all

11 papers · 1 filter

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

LaFiTe: A Generative Latent Field for 3D Native Texturing

Chia-Hao Chen, Zi-Xin Zou, Yan-Pei Cao +6

Generating high-fidelity, seamless textures directly on 3D surfaces, what we term 3D-native texturing, remains a fundamental open challenge, with the potential to overcome long-sta…

cs.CV2025

ShapeGen: Towards High-Quality 3D Shape Synthesis

Yangguang Li, Xianglong He, Zi-Xin Zou +4

Inspired by generative paradigms in image and video, 3D shape generation has made notable progress, enabling the rapid synthesis of high-fidelity 3D assets from a single image. How…

cs.CV2025

GeoSAM2: Unleashing the Power of SAM2 for 3D Part Segmentation

Ken Deng, Yunhan Yang, Jingxiang Sun +4

We introduce GeoSAM2, a prompt-controllable framework for 3D part segmentation that casts the task as multi-view 2D mask prediction. Given a textureless object, we render normal an…

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.CV2025

SeqTex: Generate Mesh Textures in Video Sequence

Ze Yuan, Xin Yu, Yangtian Sun +4

Training native 3D texture generative models remains a fundamental yet challenging problem, largely due to the limited availability of large-scale, high-quality 3D texture datasets…