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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 261–270 of 280 papers

TitleStatusHype
LeFusion: Controllable Pathology Synthesis via Lesion-Focused Diffusion ModelsCode0
EnhanceNet: Single Image Super-Resolution Through Automated Texture SynthesisCode0
A note on the evaluation of generative modelsCode0
A geometrically aware auto-encoder for multi-texture synthesisCode0
A Generative Model for Texture Synthesis based on Optimal Transport between Feature DistributionsCode0
Semantics-Aligned Representation Learning for Person Re-identificationCode0
Learning Texture Manifolds with the Periodic Spatial GANCode0
Kernelized Similarity Learning and Embedding for Dynamic Texture SynthesisCode0
TextureGAN: Controlling Deep Image Synthesis with Texture PatchesCode0
Does resistance to style-transfer equal Global Shape Bias? Measuring network sensitivity to global shape configurationCode0
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