Introduction to image inpainting with deep learning

In this article, we are going to learn how to do “image inpainting”, i.e. fill in missing parts of images precisely using deep learning. We’ll first discuss what image inpainting really means and the possible use cases that it can cater to . Next we’ll discuss some traditional image inpainting techniques and their shortcomings. Finally, we’ll see how to train a neural network that is capable of performing image inpainting with the CIFAR10 dataset. Here is the brief outline of the article:

• Introduction to image inpainting

• Traditional computer vision-based approaches

• Deep learning-based approaches – Vanilla Autoencoders and Partial convolutions

• Future directions and ending note

​🤠 Read the full article here.

​😼 Check out the GitHub repo here.

In colaboration with Sayak Paul.