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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 251–280 of 280 papers

TitleStatusHype
Awesome Typography: Statistics-Based Text Effects TransferCode0
Texture Synthesis with Recurrent Variational Auto-EncoderCode0
Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial NetworksCode0
Long Range Constraints for Neural Texture Synthesis Using Sliced Wasserstein LossCode0
Fine-Grained Multi-View Hand Reconstruction Using Inverse RenderingCode0
TexTailor: Customized Text-aligned Texturing via Effective ResamplingCode0
Texture Synthesis with Spatial Generative Adversarial NetworksCode0
Finding Biological Plausibility for Adversarially Robust Features via Metameric TasksCode0
Fast Texture Synthesis via Pseudo OptimizerCode0
Enhancing Object Coherence in Layout-to-Image SynthesisCode0
LeFusion: Controllable Pathology Synthesis via Lesion-Focused Diffusion ModelsCode0
EnhanceNet: Single Image Super-Resolution Through Automated Texture SynthesisCode0
A note on the evaluation of generative modelsCode0
A geometrically aware auto-encoder for multi-texture synthesisCode0
A Generative Model for Texture Synthesis based on Optimal Transport between Feature DistributionsCode0
Semantics-Aligned Representation Learning for Person Re-identificationCode0
Learning Texture Manifolds with the Periodic Spatial GANCode0
Kernelized Similarity Learning and Embedding for Dynamic Texture SynthesisCode0
TextureGAN: Controlling Deep Image Synthesis with Texture PatchesCode0
Does resistance to style-transfer equal Global Shape Bias? Measuring network sensitivity to global shape configurationCode0
3D microstructural generation from 2D images of cement paste using generative adversarial networksCode0
High resolution neural texture synthesis with long range constraintsCode0
Stable and Controllable Neural Texture Synthesis and Style Transfer Using Histogram LossesCode0
Texture Generation Using A Graph Generative Adversarial Network And Differentiable RenderingCode0
DRAN: Detailed Region-Adaptive Normalization for Conditional Image SynthesisCode0
StructureFlow: Image Inpainting via Structure-aware Appearance FlowCode0
Three-D Safari: Learning to Estimate Zebra Pose, Shape, and Texture from Images "In the Wild"Code0
Texture Interpolation for Probing Visual PerceptionCode0
TileGAN: Synthesis of Large-Scale Non-Homogeneous TexturesCode0
Deep Audio PriorCode0
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