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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 101–110 of 280 papers

TitleStatusHype
Co-occurrence Based Texture SynthesisCode0
Long Range Constraints for Neural Texture Synthesis Using Sliced Wasserstein LossCode0
Enhancing Object Coherence in Layout-to-Image SynthesisCode0
EnhanceNet: Single Image Super-Resolution Through Automated Texture SynthesisCode0
High resolution neural texture synthesis with long range constraintsCode0
Emotion-Controllable Generalized Talking Face Generation—0
EgoRenderer: Rendering Human Avatars from Egocentric Camera Images—0
DynTypo: Example-Based Dynamic Text Effects Transfer—0
DyNCA: Real-time Dynamic Texture Synthesis Using Neural Cellular Automata—0
Dynamic Texture Synthesis by Incorporating Long-range Spatial and Temporal Correlations—0
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