A Deep-learning Project to remove human face masks and generate the left behind region (facial inpainting)
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Updated
Jan 29, 2022 - Jupyter Notebook
A Deep-learning Project to remove human face masks and generate the left behind region (facial inpainting)
Globally and Locally Consistent Image Completion using CNNs and GANs
The main objective of this project is to present interactive image editing tools using a new randomized algorithm for quickly finding approximate nearest neighbor matches between image patches. This algorithm forms the basis for a variety of tools – that can be used together in the context of a high-level image editing application.
Pluralistic Image Completion for Anomaly Detection (Med. Image Anal. 2023)
In this project I will be using 3 inpainting methods on MIT Places Dataset.
Implement dcgan by tensorflow to complete image
This is a implement of the Siggraph2017 paper: "Globally and Locally Consistent Image Completion"
This is our code for our project on Image Completion using Deep Convolutional Generative Adversarial Networks (DCGANs)
"Globally and Locally Consistent Image Completion" with Tensorflow2 Keras
Image completion with Torch
Image Completion is the task of filling missing parts of a given image with the help of information from the known parts of the image. This is an application that takes an image with a missing part as input and gives a completed image as the result.
NTIRE 2022 - Image Inpainting Challenge
pytorch implementation of the paper ``Large Scale Image Completion via Co-Modulated Generative Adversarial Networks"
A Deep Image Completion Model for Recovering Various Corrupted Images
The pytorch implementation of the paper "text-guided neural image inpainting" at MM'2020 (oral)
Source code of AAAI 2020 paper 'Learning to Incorporate Structure Knowledge for Image Inpainting'
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