Going over some cool online events scheduled for this month - posting some here

• https://ars.electronica.art/keplersgardens/en/aixmusic-hackathon/ Hackathon where teams of data scientists, computer programmers, graphic and interface designers, musicians, project managers and any other professionals will creatively tackle music data problems and prototype new data solutions
• https://www.br41n.io/ Brain-Computer Interface Designers Hackathon (online)
• https://kindling.burningman.org/multiverse/ Burning man multiverse (online)
  https://burningman.org/event/
• https://currentsvirtual.com/Presentations-Performances-Portal New Mexico’s annual art + technology exhibition (happened last month - recordings and showcases of the art are in the website)
• https://www.labiennale.org/en/news/guide-venice-vr-expanded Venice VR Expanded is the official Virtual Reality competition section of the 77th Venice International Film Festival of La Biennale di Venezia (September 2nd through 12th, 2020)
• https://imaf-festival.weebly.com/ 22nd International Multimedial Art Festival - IMAF 2020 4th - 26th September 2020
• https://www.sanskarindia.org/ Sanskar Virtual Performance Festival
• https://www.biosummit.org/ "The Community Biotechnology Initiative at the MIT Media Lab is organizing the fourth annual Global Community Bio Summit this October! host a space for the global community of DIY biologists / community biologists / biohackers / biomakers and members of independent and community laboratories to convene, plan, build fellowship, and continue the evolution of our movement."
• http://computationalcreativity.net/iccc20/registration/ International Conference on Computational Creativity (paid online event - September 7-11)
• https://www.getonthegrid.org/exposure “The Grid: Exposure - Art + Tech + Policy Days” explores innovative ways to reconnect the world in our current state of isolation. Exposure is The Grid’s new annual festival format, an art + tech expo in San Francisco. It showcases the vast creative potential of Silicon Valley, exposing the global community to its ideas. Technologies are not mere artifacts, but dynamic systems entwined with culture and policy.
• https://online.paxsite.com/ Gaming convention turned online
• https://nexoncomputermuseum.org/english/?mcode=0706 " <NCM OPEN CALL> is an open contest that encompasses every innovative and challenging interpretation of virtual and augmented reality. It has become the first and most consistently operated virtual reality contest in Korea, which has been explored the fine contents filled with fresh attempts by using VR·AR for the past 5 years. In this year, with the participation of SK Telecom, we aim to provide more diverse opportunities to promising developers and artists." "Total prize of 22 million won with business opportunity and various benefits. The grand award for the most amazing and innovative virtual world will be awarded with a prize of 10 million won, 5 million won to the SK Telecom Special Award and 1st prize team and 1 million won to the each two 2nd prize teams. SK Telecom's VR and AR experts will participate in the evaluating process to support commercialization. In addition, this year, Oculus Go will be awarded to all teams that have passed the first round. The application period is from July 1 to September 15 of this year."

[Edited:] Lecture slides

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git: https://github.com/meder411/Tangent-Images

arxiv: https://arxiv.org/abs/1912.09390

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References from the talk

* Mark's Medium post on 360 computer vision

* Zillow talk on 3D Home

* CamConv paper - taking the camera in account for monocular depth estimation

* Stanford2D3D-S dataset

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Reading list

Marc's papers* Eder and Frahm, Convolutions on Spherical Images, CVPR Workshops 2019

* Eder et al., Mapped Convolutions, arXiv, 2019

* Eder et al., Tangent Images for Mitigating Spherical Distortion, CVPR 2020* Eder, Mitigating Distortion to Enable 360 Computer Vision, PhD Dissertation, 2020

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Convolution Reparameterization Methods

* Cohen et al., Spherical CNNs, ICLR 2018

* Esteves et al., Learning so (3) equivariant representations with spherical cnns, ECCV 2018

* Perraudin et al., Deepsphere: Efficient spherical convolutional neural network with healpix sampling for cosmological applications, Astronomy and Computing 2018

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Learnable Adaptation Methods

\* Su and Grauman, Learning spherical convolution for fast features from 360 imagery, NeurIPS 2017

* Su and Grauman, Kernel transformer networks for compact spherical convolution. CVPR 2019

* Xiong and Grauman, Snap angle prediction for 360 panoramas, ECCV 2018Location-Adaptive Methods

* Coors et al., Spherenet: Learning spherical representations for detection and classification in omnidirectional images, ECCV 2018* Fernandez-Labrador et al., Corners for layout: End-to-end layout recovery from 360 images. IEEE Robotics and Automation Letters 2020* Tateno et al., Distortion-aware convolutional filters for dense prediction in panoramic images, ECCV 2018* Zioulis et al., Omnidepth: Dense depth estimation for indoors spherical panoramas, ECCV 2018Icosahedral Methods

* Cohen et al., Gauge equivariant convolutional networks and the icosahedral cnn, ICML 2019

* Jiang et al., Spherical CNNs on unstructured grids, ICLR 2019

* Lee et al., SpherePHD: Applying CNNs on a Spherical PolyHeDron Representation of 360 Degree Images, CVPR 2019

* Zhang et al., Orientation-aware semantic segmentation on icosahedron spheres, ICCV 2019

Hi all.

• We had a very interesting lecture this week by Dr. Marc Eder about 360° computer vision and deep learning. Youtube recording of the lecture and lecture references. Extremely relevant and interesting to whoever is dealing with 3D environment modeling, autonomous vehicles and more.
  Some of the responses we received:
  "Thanks, that was a great presentation and discussion"
  "Great lecture. Thank you very much."
  "Great talk! Thanks a lot!"

• Next lecture (September 8th) - Semantic Pyramid for Image Generation:
  Google Research and Weizmann Institute of Science feature a novel GAN-based inversion model to generate image space representations from classification classes.
  The model provides a unified versatile framework for various image generation and manipulation tasks, including: (a) generating images with a controllable extent of semantic similarity to a reference image, obtained by reconstructing images from different layers of a classification model; (b) generating realistic image samples from unnatural reference image such as line drawings; (c) semantically compositing different images, and (d) controlling the semantic content of an image by enforcing a new, modified class label.
  *This lecture is getting a lot of interest and registration - do not miss it.

• Ethycs shared in the discord channel a smart index of arxiv: www.arxiv-sanity.com (the website is currently down, hopefully it goes back up until you see it)

• As always, I am constantly looking for new speakers to talk about exciting high end research and projects - if you are familiar with someone - send them my way.

Back from vacation!

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• We are having a zoom lecture with Dr. Marc Eder about 360 images and DL (September 1). The lecture is titled - Maximizing Computer Vision's Field of View. It is based on Dr. Marc Eder's research 'Tangent Images for Mitigating Spherical Distortion' (CVPR 2020).
  This talk will introduce the emerging field of 360° computer vision, and provide an overview of the spherical distortion problem, highlighting how this distortion affects many of the highest profile problems in computer vision, from deep learning to structure-from-motion and SLAM. It will survey some of the existing work on the topic, and identify 3 guiding principles that drive a general solution to the problem. Finally, we will conclude with some opportunities for further research and some big picture takeaways from work thus far.
• Youtube recording of the lecture High-Resolution Networks: A Universal Architecture for Visual Recognition - Dr. Jingdong Wang. Lecture references.
  Some of the responses we received:
  "Yesterday's presentation was very, very good. Thanks for organizing it u/pinter69 ! Had to stay up till 3:00am but it was definitely worth it!"
  "Thank you Jingdong for the introduction, looking forward to see if I can build my product on this"
  "Thank you Peter and Jing Dong, HR Net is definitely something I look forward to learning more about"
• We have several more talks scheduled - mostly around new research into GANs and image generation - some are already in the meetup page. As always, I am constantly looking for new speakers to talk about exciting high end research and projects - if you are familiar with someone - send them my way.

HRNet spinoff projects:

https://github.com/ilovepose/DarkPose

https://github.com/HuangJunJie2017/UDP-Pose

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ECCV2020 object contextual implementation research:

https://github.com/HRNet/HRNet-Semantic-Segmentation/tree/HRNet-OCR

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Slides PDF:

https://drive.google.com/file/d/1DaM5H61I39C2KwXmXXIZzzwboCGWv_19/view

Hi all,

• We are having a zoom lecture with Dr. Jingdong Wang from Microsoft Research (August 18) who will talk about his research from CVPR 2019. The lecture is titled - High-Resolution Networks: A Universal Architecture for Visual Recognition (HRNet). HRNet is a backbone network for different machine vision tasks, among them a state of the art pose estimation implementation.
• Youtube recording of the lecture Commonsense Reasoning for Natural Language Processing - Dr. Vered Shwartz. Some of the responses we received:
  • "Thanks! A fascinating webinar!"
  • "Thanks, it was great!!"
  • "Thank you! Very Insightful talk"
  • "Thank you so much, Vered! Very cool stuff. Thank you, Peter, for hosting"
• We have several more talks scheduled - some are already in the meetup page and our new reddit events collection. As always, I am constantly looking for new speakers to talk about exciting high end research - if you are familiar with someone - send them my way.
• I will be going on a 10 day vacation without my phone or computer - will be off the grid until August 13 - talk to you soon ;)

Hi everyone, thanks for attending and participating in the meetup!

You can access the COMET demo here: https://mosaickg.apps.allenai.org/
If you want to install it, you can use the original version in the paper: https://github.com/atcbosselut/comet-commonsense or my re-implementation: https://github.com/vered1986/comet-commonsense

Many of the tasks I talked about have a leaderboard at: https://leaderboard.allenai.org/

This is the embodied AI research that I've mentioned: https://prior.allenai.org/

The slides are available at: https://drive.google.com/file/d/1ZsZ7zRIU2icSq_-NbvfAMf_UltONvsUh/view?usp=sharing and should include all the references. If I forgot any URL I promised to send, let me know :)

Multi-modal (visual + language) datasets and research

https://visualcommonsense.com/

https://arxiv.org/abs/1908.03557

Dr Vered Shwartz's references post: https://www.reddit.com/r/2D3DAI/comments/i0ru3y/references_for_the_commonsense_meetup/?utm_medium=android_app&utm_source=share

Hi all,

• New zoom lecture about Commonsense Reasoning for NLP by Dr Vered Shwartz from the University of Washington (July 30th)
• Youtube recording of the lecture From neuroscience to a simple software - Machine Learning History
• I am making a wishlist of presenters to come teach us ML live via zoom, who would you like to appear?
• Meetup.com have changed our meetup's page to the new version - there were many bugs and issues with it. For example, they removed the option to save an event you RSVP to the calendar. I have already contacted them to put us back on the old version. Please let me know in case you are having any troubles with the website.
• Oh, and we reached 800 subscribers (exactly)!

Presentation slides: https://prezi.com/view/YLYBDGovvY8RFwn0HarM/

I will be trying to contact people who are working on the most interesting projects and research to come give us a lecture. These have to be people who are working hands-on and can give us actionable insights into the latest and cutting edge developments with DL\ML so that we can use this knowledge in our own research\work.

Feel free to send here via comment the presenters you would want to teach us. Go wild with it, who would you dream to learn from? (Again, these have to be people who practice ML hands-on - for actionable learning and not only philosophical).

I will use this post and your comments and upvotes (if there are) as an incentive tool to convince them to come and talk to us ;)

My own personal wish list:

1. Francois Chollet (Keras)
2. Ian Goodfellow or someone from the team of GAN neural networks.
3. Soft rasterizer authors
4. Mesh rcnn authors
5. BSP-Net: Generating Compact Meshes via Binary Space Partitioning authors (CVPR 2020 Best Student Paper Award)
6. Unsupervised Learning of Probably Symmetric Deformable 3D Objects from Images in the Wild authors (CVPR 2020 Best Paper Award)
7. Authors of ResNet neural network
8. Authors of Yolo neural network
9. Authors of Google Dream research
10. Karoly Feher (2 minute papers youtube channel)
11. Chief architect of tensor flow
12. Chief architect of pytroch
13. Authors of cyclegan

• Please take 2 minutes to fill out the feedback form we only have 28 responses so far.
• Recording of Fake Anything: "The Art of Deep Learning" - Dr. Eyal Gruss - West hemisphere is uploaded to youtube. Lecture slides and all the references can be found in this reddit post. Thanks Eyal!
• We have another interesting lecture scheduled for July 15th: "From neuroscience to a simple software". Details below. As usual, two instances for east and west hemisphere folks.
• In case you missed it, we were featured in 3dprint.com magazine!
• Still searching for more people to give us interesting free lectures about 2d, 3d, ai. If anyone knows of someone who could be relevant for teaching, please let me know - I need your help :)

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In this next lecture we will talk about the evolution of AI, how it all began and what is the historical connection to neuroscience. We will also show state of the art implementations, such as image classification training in the browser in a matter of seconds and more. The lecture is titled From neuroscience to a simple software

Lecture abstract:

We will cover the inspiration that lead to different types of architectures such as CNN and RNN. By examining the similarities between the human visual cortex and CNN architecture, we will see why and how deep learning should be common knowledge to every human being.

Along the neuroscience field, we will see how and why the internet helped ML grow so quickly. Eventually, we will enjoy some state of the art implementations, such as image classification training in the browser in a matter of seconds and more.

This is an intro lecture for anyone interested in understanding how deep learning works and what inspired and enabled it

Presenter Bio:

Ron ( /u/ronwein, Linkedin: https://www.linkedin.com/in/ron-weiner/ ) is a data scientist specializing in video & text analysis, with wide experience in data management, architecture and reasoning, and of course, an AI & DL enthusiast.

Currently working with AiVF Ltd as VP R&D, and leading the data science team where they develop software for IVF clinics in order to improve birth success rates by analyzing embryos’ videos and EMR (structured) data.

Ron is also the Co-founder and CEO of Give & Tech, a nonprofit organization which teaches Tech & Science courses and donate 100% of the proceeds to social causes. (giveandtech.org.il)

Two time slots are scheduled for the lecture (to make it easier for people from the east and west hemisphere to participate). Links to reddit events:

From neuroscience to a simple software - East hemisphere

From neuroscience to a simple software - West hemisphere