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20242026
most citedTEXGen: a Generative Diffusion Model for Mesh Textures

22 citations · 24 across the 7 of their papers we have counts for

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8 papers · 1 filter

cs.CV2026

ArtiMo: Agent-Driven Articulated Mesh Animation

Chunyu Zou, Peng Dai, Yi-Hua Huang +4

Animating articulated 3D meshes via text requires satisfying strict kinematic constraints, modeling causal interactions between parts, and achieving instruction fidelity. Due to th…

cs.CV2026

PhysEditBench: A Protocol-Conditioned Benchmark for Dense Physical-Map Prediction with Image Editors

Jiaxin Yang, Yu Hou, Muxin Liu +5

Can general-purpose image editors predict physical maps from a single RGB image? General-purpose image editors differ from standard task-specific dense-prediction models: they do n…

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

VT-Intrinsic: Physics-Based Decomposition of Reflectance and Shading using a Single Visible-Thermal Image Pair

Zeqing Yuan, Mani Ramanagopal, Aswin C. Sankaranarayanan +1

Decomposing a scene into its reflectance and shading is a challenge due to the lack of extensive ground-truth data for real-world scenes. We introduce a novel physics-based approac…

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…

cs.CV202422 cited

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…