Last week one of the important conference in computer vision fields ICCV19 held on Seoul and finished. Here is the voting results about bests.

ICCV 2019 Best Papers:

* Best Paper Award (Marr Prize): SinGAN: Learning a Generative Model from a Single Natural Image

* Best Student Paper Award:
PLMP — Point-Line Minimal Problems in Complete Multi-View Visibility

* Best Paper Honorable Mentions
Paper:
Asynchronous Single-Photon 3D Imaging

South Korea has created an entire city for testing self-driving cars with 35 kinds of road test facilities. Here is the video from BuzzFeed news

NVIDIA released a PyTorch library ‘Kaolin’, which in few steps, moves 3D models into neural networks.

Now t-SNE with RAPIDs cuML 2000x speed-up over scikit-learn. But is very slightly accurate (at most ~3% error). Here is also detailed explanation about t-SNE, wich nonlinear dimensionality reduction algorithm.

RoboNet: A Dataset for Large-Scale Multi-Robot Learning (15 million video frames, 7 Robot platform).

RoboNet Project page:
https://www.robonet.wiki/

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Things you need to consider about your algorithm is working or not

https://medium.com/artificial-intelligence-solutions/so-is-your-algorithm-not-working-aa8e4ebd2066?

BMW shares AI algorithms used in production, available on GitHub

I think, every AI lovers are waiting for AI debate: Yoshua Bengio and Gary Marcus, which a decade that has revived the field of AI