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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 231–240 of 280 papers

TitleStatusHype
Semantic Image Translation for Repairing the Texture Defects of Building Models—0
Single Mesh Diffusion Models with Field Latents for Texture Generation—0
STS-GAN: Can We Synthesize Solid Texture with High Fidelity from Arbitrary 2D Exemplar?—0
Spatial Degradation-Aware and Temporal Consistent Diffusion Model for Compressed Video Super-Resolution—0
Step1X-3D: Towards High-Fidelity and Controllable Generation of Textured 3D Assets—0
Stochastic Geometry Models for Texture Synthesis of Machined Metallic Surfaces: Sandblasting and Milling—0
Non-Stationary Texture Synthesis by Adversarial ExpansionCode0
Style-Transfer via Texture-SynthesisCode0
Two-Stream Convolutional Networks for Dynamic Texture SynthesisCode0
Co-occurrence Based Texture SynthesisCode0
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