The AI Monthly Top 3 — July 2021
The 3 most interesting AI papers of July 2021 with video demos, short articles, code, and paper reference.
Here are the 3 most interesting research papers of the month, in case you missed any of them. It is a curated list of the latest breakthroughs in AI and Data Science by release date with a clear video explanation, link to a more in-depth article, and code (if applicable). Enjoy the read, and let me know if I missed any important papers in the comments, or by contacting me directly on LinkedIn!
If you’d like to read more research papers as well, I recommend you read my article where I share my best tips for finding and reading more research papers.
Paper #1:
CVPR 2021 Best Paper Award: GIRAFFE - Controllable Image Generation [1]
Using a modified GAN architecture, they can move objects in the image without affecting the background or the other objects!
Watch the video
A short read version
Louis Bouchard
Code: https://github.com/autonomousvision/giraffe
Paper #2:
OpenAI’s New Code Generator: GitHub Copilot (and Codex) | This AI Generates Code From Words [2]
Find out how this new model from OpenAI Generates Code From Words!
Watch the video
A short read version
Louis Bouchard
Code: https://copilot.github.com/
Paper #3:
How Apple Photos Recognizes People in Private Photos Using Machine Learning [3]
Using multiple machine learning-based algorithms running privately on your device, Apple allows you to accurately curate and organize your images and videos on iOS 15.
Watch the video
A short read version
Louis Bouchard
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References
[1] Michael Niemeyer and Andreas Geiger, (2021), “GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields”, Published in CVPR 2021.
[2] OpenAI’s Codex/copilot paper: https://arxiv.org/pdf/2107.03374.pdf
[3] Apple, “Recognizing People in Photos Through Private On-Device Machine Learning”, (2021), https://machinelearning.apple.com/research/recognizing-people-photos