Loading repository data…
louisfb01 / repository
A curated list of the top 10 computer vision papers in 2021 with video demos, articles, code and paper reference.
While the world is still recovering, research hasn't slowed its frenetic pace, especially in the field of artificial intelligence. More, many important aspects were highlighted this year, like the ethical aspects, important biases, governance, transparency and much more. Artificial intelligence and our understanding of the human brain and its link to AI are constantly evolving, showing promising applications improving our life's quality in the near future. Still, we ought to be careful with which technology we choose to apply.
"Science cannot tell us what we ought to do, only what we can do."- Jean-Paul Sartre, Being and Nothingness
Here are my top 10 of the most interesting research papers of the year in computer vision, in case you missed any of them. In short, it is basically a curated list of the latest breakthroughs in AI and CV 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!
The complete reference to each paper is listed at the end of this repository.
Maintainer: louisfb01
Subscribe to my newsletter - The latest updates in AI explained every week.
Feel free to message me any interesting paper I may have missed to add to this repository.
Tag me on Twitter @Whats_AI or LinkedIn @Louis (What's AI) Bouchard if you share the list!
Missed last year? Check this out: 2020: A Year Full of Amazing AI papers- A Review
👀 If you'd like to support my work and use W&B (for free) to track your ML experiments and make your work reproducible or collaborate with a team, you can try it out by following this guide! Since most of the code here is PyTorch-based, we thought that a QuickStart guide for using W&B on PyTorch would be most interesting to share.
👉Follow this quick guide, use the same W&B lines in your code or any of the repos below, and have all your experiments automatically tracked in your w&b account! It doesn't take more than 5 minutes to set up and will change your life as it did for me! Here's a more advanced guide for using Hyperparameter Sweeps if interested :)
🙌 Thank you to Weights & Biases for sponsoring this repository and the work I've been doing, and thanks to any of you using this link and trying W&B!
A curated list of the latest breakthroughs in AI by release date with a clear video explanation, link to a more in-depth article, and code.
2021: A Year Full of Amazing AI papers- A Review
OpenAI successfully trained a network able to generate images from text captions. It is very similar to GPT-3 and Image GPT and produces amazing results.
Tl;DR: They combined the efficiency of GANs and convolutional approaches with the expressivity of transformers to produce a powerful and time-efficient method for semantically-guided high-quality image synthesis.
Will Transformers Replace CNNs in Computer Vision? In less than 5 minutes, you will know how the transformer architecture can be applied to computer vision with a new paper called the Swin Transformer.
"I will openly share everything about deep nets for vision applications, their successes, and the limitations we have to address."
The next step for view synthesis: Perpetual View Generation, where the goal is to take an image to fly into it and explore the landscape!
Properly relight any portrait based on the lighting of the new background you add. Have you ever wanted to change the background of a picture but have it look realistic? If you’ve already tried that, you already know that it isn’t simple. You can’t just take a picture of yourself in your home and change the background for a beach. It just looks bad and not realistic. Anyone will just say “that’s photoshopped” in a second. For movies and professional videos, you need the perfect lighting and artists to reproduce a high-quality image, and that’s super expensive. There’s no way you can do that with your own pictures. Or can you?
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.
This model takes a picture, understands which particles are supposed to be moving, and realistically animates them in an infinite loop while conserving the rest of the picture entirely still creating amazing-looking videos like this one...
Using a modified GAN architecture, they can move objects in the image without affecting the background or the other objects!
TimeLens can understand the movement of the particles in-between the frames of a video to reconstruct what really happened at a speed even our eyes cannot see. In fact, it achieves results that our intelligent phones and no other models could reach before!
Selected from shared topics, language and repository description—not editorial ratings.
louisfb01 /
A curated list of the latest breakthroughs in AI (in 2021) by release date with a clear video explanation, link to a more in-depth article, and code.