Awesome-Image-Inpainting VS ABigSurvey

Compare Awesome-Image-Inpainting vs ABigSurvey and see what are their differences.

Awesome-Image-Inpainting

A curated list of image inpainting and video inpainting papers and resources (by zengyh1900)

ABigSurvey

A collection of 1000+ survey papers on Natural Language Processing (NLP) and Machine Learning (ML). (by NiuTrans)
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Awesome-Image-Inpainting ABigSurvey
3 1
1,736 1,951
- 1.5%
2.7 3.8
3 months ago about 1 month ago
Python
- GNU General Public License v3.0 only
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

Awesome-Image-Inpainting

Posts with mentions or reviews of Awesome-Image-Inpainting. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-08-29.
  • MagicEdit: High-Fidelity Temporally Coherent Video Editing
    2 projects | news.ycombinator.com | 29 Aug 2023
    I have been reading a lot of adjacent papers to this recently. Here is a useful collection for anyone interested: https://github.com/zengyh1900/Awesome-Image-Inpainting

    I have noticed an overwhelming trend that the vast majority of authors tend to be Chinese sounding names even when associated with an US based university. Obviously some of those could be Americans as well but it stood out to such a degree I was curious if anyone had any insight.

    Also if there is code (this projects links to github but it's empty), it tends to be basically abandonware once these papers are published with no effort towards commercializing or turning into healthy open source projects for some reason.

  • Implemented approaches to reconstructing missing parts in an image
    1 project | /r/computervision | 10 Feb 2022
    Image in-painting is the keyword I think you are looking for. This github repo has a bunch of links to different implementations.
  • [Research] NN to extrapolate painting
    1 project | /r/MachineLearning | 13 Feb 2021
    I am not an expert on this, but this repo lists the latest Image Inpainting methods https://github.com/1900zyh/Awesome-Image-Inpainting.

ABigSurvey

Posts with mentions or reviews of ABigSurvey. We have used some of these posts to build our list of alternatives and similar projects.
  • Becoming a ML/DL researcher
    1 project | /r/learnmachinelearning | 20 Feb 2021
    Find out a couple of survey papers (e.g., https://github.com/NiuTrans/ABigSurvey) and start reading them. Don't go into the details at first. Develop a broader picture - what is important, why is it important, is it worth applying ML to that topic, and most importantly if given that problem how would you approach it.

What are some alternatives?

When comparing Awesome-Image-Inpainting and ABigSurvey you can also consider the following projects:

DeepMosaics - Automatically remove the mosaics in images and videos, or add mosaics to them.

Machine-Learning-Tutorials - machine learning and deep learning tutorials, articles and other resources

DeepCreamPy - Decensoring Hentai with Deep Neural Networks

start-machine-learning - A complete guide to start and improve in machine learning (ML), artificial intelligence (AI) in 2024 without ANY background in the field and stay up-to-date with the latest news and state-of-the-art techniques!

ProPainter - [ICCV 2023] ProPainter: Improving Propagation and Transformer for Video Inpainting

GNNPapers - Must-read papers on graph neural networks (GNN)

awesome-ml4co - Awesome machine learning for combinatorial optimization papers.

PEN-Net-for-Inpainting - [CVPR'2019] PEN-Net: Learning Pyramid-Context Encoder Network for High-Quality Image Inpainting

StableVideo - [ICCV 2023] StableVideo: Text-driven Consistency-aware Diffusion Video Editing