Image completion with Torch
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Updated
Apr 13, 2017 - Lua
Image completion with Torch
This is our code for our project on Image Completion using Deep Convolutional Generative Adversarial Networks (DCGANs)
Image completion using deep convolutional generative adversarial nets in tensorflow
Implement dcgan by tensorflow to complete image
A Deep Image Completion Model for Recovering Various Corrupted Images
This is a implement of the Siggraph2017 paper: "Globally and Locally Consistent Image Completion"
Image Completion using PatchMatch algorithm
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.
"Globally and Locally Consistent Image Completion" with Tensorflow2 Keras
In this project I will be using 3 inpainting methods on MIT Places Dataset.
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.
Source code of AAAI 2020 paper 'Learning to Incorporate Structure Knowledge for Image Inpainting'
[ICLR 2021, Spotlight] Large Scale Image Completion via Co-Modulated Generative Adversarial Networks
A Deep-learning Project to remove human face masks and generate the left behind region (facial inpainting)
CR-Fill: Generative Image Inpainting with Auxiliary Contextual Reconstruction. ICCV 2021
pytorch implementation of the paper ``Large Scale Image Completion via Co-Modulated Generative Adversarial Networks"
NTIRE 2022 - Image Inpainting Challenge
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