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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 121–130 of 280 papers

TitleStatusHype
Generative AI meets 3D: A Survey on Text-to-3D in AIGC Era—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
3DGen: Triplane Latent Diffusion for Textured Mesh GenerationCode2
A geometrically aware auto-encoder for multi-texture synthesisCode0
Neural Texture Synthesis With Guided CorrespondenceCode1
ClipFace: Text-guided Editing of Textured 3D Morphable ModelsCode1
DyNCA: Real-time Dynamic Texture Synthesis Using Neural Cellular Automata—0
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