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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 241–250 of 280 papers

TitleStatusHype
Conditional Generative ConvNets for Exemplar-based Texture SynthesisCode0
Hard Example Generation by Texture Synthesis for Cross-domain Shape Similarity LearningCode0
A Structure-Guided Diffusion Model for Large-Hole Image CompletionCode0
μNCA: Texture Generation with Ultra-Compact Neural Cellular AutomataCode0
Local Padding in Patch-Based GANs for Seamless Infinite-Sized Texture SynthesisCode0
Generalized Rectifier Wavelet Covariance Models For Texture SynthesisCode0
Texture Synthesis Through Convolutional Neural Networks and Spectrum ConstraintsCode0
Texture Synthesis Using Convolutional Neural NetworksCode0
Towards Metamerism via Foveated Style TransferCode0
FrankenGAN: Guided Detail Synthesis for Building Mass-Models Using Style-Synchronized GANsCode0
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