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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 181–190 of 280 papers

TitleStatusHype
Texture Generation Using Dual-Domain Feature Flow with Multi-View Hallucinations—0
Texture Image Synthesis Using Spatial GAN Based on Vision Transformers—0
TextureMeDefect: LLM-based Defect Texture Generation for Railway Components on Mobile Devices—0
Texture Mixing by Interpolating Deep Statistics via Gaussian Models—0
Texture Modelling with Nested High-order Markov-Gibbs Random Fields—0
Texture Representations for Image and Video Synthesis—0
Texture Synthesis Guided Deep Hashing for Texture Image Retrieval—0
Texture Synthesis Using Shallow Convolutional Networks with Random Filters—0
Texture synthesis via projection onto multiscale, multilayer statistics—0
TGHop: An Explainable, Efficient and Lightweight Method for Texture Generation—0
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