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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 51–75 of 280 papers

TitleStatusHype
Iterative Token Evaluation and Refinement for Real-World Super-ResolutionCode1
Towards Universal Texture Synthesis by Combining Texton Broadcasting with Noise Injection in StyleGAN-2Code1
Everything's Talkin': Pareidolia Face ReenactmentCode1
UV-IDM: Identity-Conditioned Latent Diffusion Model for Face UV-Texture GenerationCode1
Keys to Better Image Inpainting: Structure and Texture Go Hand in HandCode1
HiPrompt: Tuning-free Higher-Resolution Generation with Hierarchical MLLM PromptsCode1
3D-FRONT: 3D Furnished Rooms with layOuts and semaNTicsCode1
Generating Non-Stationary Textures using Self-RectificationCode1
Human Parsing Based Texture Transfer from Single Image to 3D Human via Cross-View ConsistencyCode1
Learning Texture Transformer Network for Image Super-ResolutionCode1
ShaDDR: Interactive Example-Based Geometry and Texture Generation via 3D Shape Detailization and Differentiable RenderingCode1
Emotion-Controllable Generalized Talking Face Generation—0
EgoRenderer: Rendering Human Avatars from Egocentric Camera Images—0
A Procedural Texture Generation Framework Based on Semantic Descriptions—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
Dynamic Neural Style Transfer for Artistic Image Generation using VGG19—0
Dual Pipeline Style Transfer with Input Distribution Differentiation—0
Color and Texture Dual Pipeline Lightweight Style Transfer—0
DTSGAN: Learning Dynamic Textures via Spatiotemporal Generative Adversarial Network—0
DressCode: Autoregressively Sewing and Generating Garments from Text Guidance—0
Cloth2Tex: A Customized Cloth Texture Generation Pipeline for 3D Virtual Try-On—0
Dress-1-to-3: Single Image to Simulation-Ready 3D Outfit with Diffusion Prior and Differentiable Physics—0
DreamSpace: Dreaming Your Room Space with Text-Driven Panoramic Texture Propagation—0
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