Inpainting and restoration

Inpainting is a conservation process where damaged, deteriorating, or missing parts of an artwork are filled in to present a complete image

Resources

• https://en.wikipedia.org/wiki/Inpainting
• https://paperswithcode.com/task/image-restoration
• https://www.nvidia.com/research/inpainting/
• An Introduction to Image Inpainting using Deep Learning
• GANs and Missing Data Imputation

References

• #PAPER #REVIEW Image inpainting: A review (Elharrouss 2019)

CNN-based

See AI/Computer Vision/Deep image prior

• #PAPER Feature Learning by Inpainting (Pathak 2016)
  • #CODE https://github.com/pathak22/context-encoder
• #PAPER Image Inpainting for Irregular Holes Using Partial Convolutions (Liu 2018)
  • https://nv-adlr.github.io/publication/partialconv-inpainting
  • #CODE https://github.com/NVIDIA/partialconv
  • #CODE https://github.com/naoto0804/pytorch-inpainting-with-partial-conv
  • #CODE https://github.com/MathiasGruber/PConv-Keras
  • #CODE Various Keras Layers that can be used with TensorFlow 2.x
• #PAPER Partial Convolution based Padding (Liu 2018)
• #PAPER Probabilistic Semantic Inpainting with Pixel Constrained CNNs (Dupont 2019)
  • #CODE https://github.com/Schlumberger/pixel-constrained-cnn-tf
• #PAPER A Flexible Deep CNNs Framework for Image Restoration (2020)
  • https://www.researchgate.net/profile/Zhi_Jin6/publication/335500109_A_Flexible_Deep_CNN_Framework_for_Image_Restoration/links/5da7c1a9299bf1c1e4c837c3/A-Flexible-Deep-CNN-Framework-for-Image-Restoration.pdf
• #PAPER Deep learning-Based 3D inpainting of brain MR images (Kwan Kang 2021)

GAN-based

• #PAPER VIGAN: Missing View Imputation with Generative Adversarial Networks (Shang 2017)
  • #CODE https://github.com/chaoshangcs/VIGAN
• #PAPER Patch-Based Image Inpainting with GANs (Demir 2018)
• #PAPER GAIN: Missing Data Imputation using GANs (Yoon 2018)
  • #CODE https://github.com/jsyoon0823/GAIN
• #PAPER MisGAN: Learning from Incomplete Data with Generative Adversarial Networks (Li 2019)
• #PAPER CollaGAN : Collaborative GAN for Missing Image Data Imputation (Li 2019)
• #PAPER DeepGIN: Deep Generative Inpainting Network for Extreme Image Inpainting (Li 2020)
  • #CODE https://github.com/rlct1/DeepGIN
  • https://medium.com/analytics-vidhya/review-of-deepgin-deep-generative-inpainting-network-for-extreme-image-inpainting-de5b191562b0
• #PAPER The image inpainting algorithm used on multi-scale generative adversarial networks and neighbourhood (Mo 2020)