The AI Monthly Top 3 — April 2021

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!


Paper #1:

Create 3D Models from Images! GANverse3D & NVIDIA Omniverse [1]

This promising model called GANverse3D only needs an image to create a 3D figure that can be customized and animated!

Watch the video

A short read version

Create 3D Models from Images! GANverse3D & NVIDIA Omniverse
This promising model called GANverse3D only needs an image to create a 3D figure that can be customized and animated!

Paper #2:

What is the state of AI in computer vision? [2]

I will openly share everything about deep nets for vision applications, their successes, and the limitations we have to address.

Watch the video

A short read version

What is the state of AI in computer vision?
I will openly share everything about deep nets for vision applications, their successes, and the limitations we have to address.

Paper #3:

Infinite Nature: Fly into an image and explore the landscape [3]

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!

Watch the video

A short read version

Infinite Nature: Fly into an image and explore the landscape
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!

Code: https://github.com/microsoft/Swin-Transformer
Colab demo you can try right now!


Bonus paper:

An Amputee with an AI-Powered Hand! 🦾[Bonus]

With this AI-powered nerve interface, the amputee can control a neuroprosthetic hand with life-like dexterity and intuitiveness.

Watch the video

A short read version

An Amputee with an AI-Powered Hand! 🦾
With this AI-powered nerve interface, the amputee can control a neuroprosthetic hand with life-like dexterity and intuitiveness.

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References

[1] Zhang et al., (2020), “IMAGE GANS MEET DIFFERENTIABLE RENDERING FOR INVERSE GRAPHICS AND INTERPRETABLE 3D NEURAL RENDERING”: https://arxiv.org/pdf/2010.09125.pdf

[2] Yuille, A.L., and Liu, C., 2021. Deep nets: What have they ever done for vision?. International Journal of Computer Vision, 129(3), pp.781–802, https://arxiv.org/abs/1805.04025.

[3] Liu, A., Tucker, R., Jampani, V., Makadia, A., Snavely, N. and Kanazawa, A., 2020. Infinite Nature: Perpetual View Generation of Natural Scenes from a Single Image, https://arxiv.org/pdf/2012.09855.pdf

[Bonus] Nguyen & Drealan et al. (2021) A Portable, Self-Contained Neuroprosthetic Hand with Deep Learning-Based Finger Control: https://arxiv.org/abs/2103.13452​