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Texture Synthesis

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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

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/harunshimanto/Neural-Style-Transfer-of-Artistic-Style

Incorporating long-range consistency in CNN-based texture generation

https://github.com/honzukka/texture-synthesis-pytorch

Texture Synthesis Using Convolutional Neural Networks

https://github.com/imransalam/style-transfer-tensorflow-2.0

Stable and Controllable Neural Texture Synthesis and Style Transfer Using Histogram Losses

https://github.com/inzouzouwetrust/IMA_RWCNN_project

Texture Synthesis Using Convolutional Neural Networks

https://github.com/janesjanes/Pytorch-TextureGAN

TextureGAN: Controlling Deep Image Synthesis with Texture Patches

https://github.com/jessemelpolio/non-stationary_texture_syn

Non-Stationary Texture Synthesis by Adversarial Expansion

https://github.com/jsonkung/style-transfer-texture-synthesis

Style-Transfer via Texture-Synthesis

https://github.com/kaziwasaleh/mask-guided

TextureGAN: Controlling Deep Image Synthesis with Texture Patches

https://github.com/kpandey008/DCGANS

A note on the evaluation of generative models

https://github.com/magnuspetersen/mnnca

Texture Generation with Neural Cellular Automata

https://github.com/mdsarfarazulh/deep-texture-synthesis-cnn-keras

Texture Synthesis Using Convolutional Neural Networks

https://github.com/meet-minimalist/Texture-Synthesis-Using-Convolutional-Neural-Networks

Texture Synthesis Using Convolutional Neural Networks

https://github.com/msmsajjadi/EnhanceNet-Code

EnhanceNet: Single Image Super-Resolution Through Automated Texture Synthesis

https://github.com/ngonthier/multiresolution_texture

Texture Synthesis Using Convolutional Neural Networks

https://github.com/nirvanalan/ln3diff

3DGen: Triplane Latent Diffusion for Textured Mesh Generation

https://github.com/nmichlo/lightning-nca

Texture Generation with Neural Cellular Automata

https://github.com/nsarafianos/Garment3DGen

Garment3DGen: 3D Garment Stylization and Texture Generation

https://github.com/oist/psgan

Learning Texture Manifolds with the Periodic Spatial GAN

https://github.com/paulwarkentin/pytorch-neural-doodle

Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesis

https://github.com/rinnakk/japanese-stable-diffusion

Pretraining is All You Need for Image-to-Image Translation

https://github.com/ryanwebster90/image-synthesis-lab2

Texture Synthesis Using Convolutional Neural Networks

https://github.com/ryanwebster90/texture-synthesis-lab

Texture Synthesis Using Convolutional Neural Networks

https://github.com/ryersonvisionlab/two-stream-dyntex-synth

Texture Synthesis Using Convolutional Neural Networks

https://github.com/sar-gupta/convisualize_nb

Texture Synthesis Using Convolutional Neural Networks

https://github.com/shiming-chen/Similariy-DT

Kernelized Similarity Learning and Embedding for Dynamic Texture Synthesis

https://github.com/soumik12345/Pix2Pix

Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks

https://github.com/swift-n-brutal/syntex

Texture Synthesis Using Convolutional Neural Networks

https://github.com/trsvchn/deep-textures

Texture Synthesis Using Convolutional Neural Networks

https://github.com/ty625911724/texture_generation_master

Incorporating long-range consistency in CNN-based texture generation

https://github.com/ubergmann/spatial_gan

Texture Synthesis with Spatial Generative Adversarial Networks

https://github.com/viriditass/Style-transfer

Stable and Controllable Neural Texture Synthesis and Style Transfer Using Histogram Losses

https://github.com/wuyx517/VQVAE_image_inpainting

Generating Diverse Structure for Image Inpainting With Hierarchical VQ-VAE

https://github.com/wzm2256/cgCNN

Conditional Generative ConvNets for Exemplar-based Texture Synthesis

https://github.com/xuefusiji/badrefsr

Learning Texture Transformer Network for Image Super-Resolution

https://github.com/yangyucheng000/University/tree/main/model-3/sew_d

Towards Garment Sewing Pattern Reconstruction from a Single Image

https://github.com/yangyucheng000/cstdg

Image Inpainting via Conditional Texture and Structure Dual Generation

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.