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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 131–140 of 280 papers

TitleStatusHype
DyNCA: Real-time Dynamic Texture Synthesis Using Neural Cellular Automata—0
A Structure-Guided Diffusion Model for Large-Hole Image CompletionCode0
DeepDC: Deep Distance Correlation as a Perceptual Image Quality EvaluatorCode1
Parameter Sensitivity of Deep-Feature based Evaluation Metrics for Audio Textures—0
Keys to Better Image Inpainting: Structure and Texture Go Hand in HandCode1
Initialization and Alignment for Adversarial Texture Optimization—0
Texture Generation Using A Graph Generative Adversarial Network And Differentiable RenderingCode0
Orthonormal Convolutions for the Rotation Based Iterative Gaussianization—0
Pretraining is All You Need for Image-to-Image TranslationCode2
AvatarCLIP: Zero-Shot Text-Driven Generation and Animation of 3D AvatarsCode3
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