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Texture Synthesis

The fundamental goal of example-based Texture Synthesis is to generate a texture, usually larger than the input, that faithfully captures all the visual characteristics of the exemplar, yet is neither identical to it, nor exhibits obvious unnatural looking artifacts.

Source: Non-Stationary Texture Synthesis by Adversarial Expansion

Papers

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Showing 101–125 of 280 papers

TitleStatusHype
Towards Garment Sewing Pattern Reconstruction from a Single ImageCode2
Mesh Neural Cellular Automata—0
Text-to-3D with Classifier Score Distillation—0
TexFusion: Synthesizing 3D Textures with Text-Guided Image Diffusion Models—0
DreamSpace: Dreaming Your Room Space with Text-Driven Panoramic Texture Propagation—0
Does resistance to style-transfer equal Global Shape Bias? Measuring network sensitivity to global shape configurationCode0
Wasserstein Distortion: Unifying Fidelity and Realism—0
Color and Texture Dual Pipeline Lightweight Style Transfer—0
HumanNorm: Learning Normal Diffusion Model for High-quality and Realistic 3D Human Generation—0
Diffusion-based Holistic Texture Rectification and Synthesis—0
TwinTex: Geometry-aware Texture Generation for Abstracted 3D Architectural Models—0
Integrating GAN and Texture Synthesis for Enhanced Road Damage Detection—0
Local Padding in Patch-Based GANs for Seamless Infinite-Sized Texture SynthesisCode0
Example-Based Framework for Perceptually Guided Audio Texture Generation—0
Texture Generation on 3D Meshes with Point-UV DiffusionCode2
Cloth2Tex: A Customized Cloth Texture Generation Pipeline for 3D Virtual Try-On—0
Surface Geometry Processing: An Efficient Normal-based Detail Representation—0
ShaDDR: Interactive Example-Based Geometry and Texture Generation via 3D Shape Detailization and Differentiable RenderingCode1
Reference-based OCT Angiogram Super-resolution with Learnable Texture Generation—0
Generative AI meets 3D: A Survey on Text-to-3D in AIGC Era—0
Learning in a Single Domain for Non-Stationary Multi-Texture Synthesis—0
TUVF: Learning Generalizable Texture UV Radiance Fields—0
Generating Texture for 3D Human Avatar from a Single Image using Sampling and Refinement Networks—0
Semantic Image Translation for Repairing the Texture Defects of Building Models—0
Text2Tex: Text-driven Texture Synthesis via Diffusion ModelsCode1
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