Miscellaneous

[Airicist]

https://youtu.be/ZG9GIQgmisY

Machine Vision Bottle Cap Verification

Uploaded on Jan 13, 2009


The Q:Check Cap Verification system inspects flat and sipper caps on beverage bottles for cap presence and height, intact tamper ring, dust cap presence and fill level. The fully automated visual control of the cap area prevents drink contamination and spillage.

[Airicist]

https://youtu.be/L6Q499wxzPc

Vicente Ordonez: Language and Perceptual Categorization in Computer Vision

Published on Mar 14, 2015


Talk: Vicente Ordonez-Roman
University of North Carolina at Chapel Hill

Title: Language and Perceptual Categorization in Computer Vision

Abstract:
Recently, there has been great progress in both computer vision and natural language processing in representing and recognizing semantic units like objects, attributes, named entities, or constituents. These advances provide opportunities to create systems able to interpret and describe the visual world using natural language. This is in contrast to traditional computer vision systems, which typically output a set of disconnected labels, object locations, or annotations for every pixel in an image. The rich visually descriptive language produced by people incorporates world knowledge and human intuition that often can not be captured by other types of annotations. In this talk, I will present several approaches that explore the connections between language, perception, and vision at three levels: learning how to name objects, generating referring expressions for objects in natural scenes, and producing general image descriptions. These methods provide a framework to augment computer vision systems with linguistic information and to take advantage of the vast amount of text associated with images on the web. I will also discuss some of the intuitions from linguistics and perception behind these efforts and how they potentially connect to the larger goal of creating visual systems that can better learn from and communicate with people.

[Airicist]

Article "Predicting Daily Activities From Egocentric Images Using
Deep Learning (https://www.cc.gatech.edu/cpl/projects/dailyactivities/paper.pdf)"

by Daniel Castro, Steven Hickson, Vinay Bettadapura, Edison Thomaz
Gregory Abowd, Henrik Christensen, Irfan Essa
September 7-11, 2015

[Airicist]

Article "Deep Neural Networks are Easily Fooled:
High Confidence Predictions for Unrecognizable Images (https://arxiv.org/pdf/1412.1897v4.pdf)"

by Anh Nguyen, Jason Yosinski, Jeff Clune
2015

[Airicist]

https://youtu.be/Jh5bM5cUPQA

Microsoft Selfie (https://pr.ai/showthread.php?4302) app updated with social sharing

Published on Jan 25, 2016


The popular Microsoft Selfie app has been updated with social sharing to Facebook, Twitter, WeChat as well as native apps for iOS users. The app uses computer vision and machine learning to enhance the images you take, removing noise and auto-correcting for poor lighting.

[Airicist]

Article "Next Big Test for AI: Making Sense of the World (https://www.technologyreview.com/2016/01/26/163630/next-big-test-for-ai-making-sense-of-the-world)"
A new database will gauge progress in artificial intelligence, as computers try to grasp what’s going on in scenes shown in photographs.

by Will Knight
January 26, 2016

[Airicist]

Article "How machine vision systems and robots have influenced each other (https://www.controldesign.com/articles/2016/how-machine-vision-systems-and-robots-have-influenced-each-other)"
Is machine vision changing robots, or are robots changing machine vision?

by Mike Bacidore
April 11, 2016

[Airicist]

Article "Teaching machines to predict the future (http://news.mit.edu/2016/teaching-machines-to-predict-the-future-0621)"
Deep-learning vision system from the Computer Science and Artificial Intelligence Lab anticipates human interactions using videos of TV shows.

by Adam Conner-Simons, Rachel Gordon
June 21, 2016

[Airicist]

Article "How template matching works in robot vision (https://robohub.org/how-template-matching-works-in-robot-vision)"

by Alex Owen-Hill
June 30, 2016

[Airicist]

Article "Learning to color: Can artificial intelligence accurately colorize your black and white photos? (https://www.imaging-resource.com/news/2016/07/17/can-artificial-intelligence-accurately-colorize-your-black-and-white-photos)"

by Jeremy Gray
July 17, 2016

[Airicist]

Article "How To Fool AI Into Seeing Something That Isn’t There (https://www.wired.com/2016/07/fool-ai-seeing-something-isnt)"

by Cade Metz
July 29, 2016

[Airicist]

https://youtu.be/Pt1W_v-yQhw

Creating videos of the future

Published on Nov 29, 2016

"Creating videos of the future (http://www.csail.mit.edu/creating_videos_of_the_future)"

by Adam Conner-Simons
November 28, 2016

[Airicist]

Articles "This site transforms your doodles into atrocious cat monsters (https://thenextweb.com/dd/2017/02/22/transform-doodles-cat-monsters)"

by Alejandro Tauber
February 22, 2017

[Airicist]

Article "This artificial intelligence turns horses into zebras – and winter into summer (https://thenextweb.com/artificial-intelligence/2017/04/19/artificial-intelligence-turn-horse-zebra)"

by Mix
April 19, 2017

CycleGAN project

Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.

[Airicist]

affinelayer.com (https://affinelayer.com)

[Airicist]

Article "Automatic image retouching on your phone (http://news.mit.edu/2017/automatic-image-retouching-phone-0802)"
System can apply a range of styles in real-time, so that the viewfinder displays the enhanced image.

by Larry Hardesty
August 1, 2017

[Airicist]

Article "4D Camera Could Improve Robot Vision, Virtual Reality and Self-driving Cars (http://ucsdnews.ucsd.edu/pressrelease/4d_camera_could_improve_robot_vision_virtual_reality_and_self_driving_cars)"

by Liezel Labios
August 4, 2017

[Airicist]

https://youtu.be/LBezOcnNJ68

NVIDIA's AI makes amazing slow-mo videos

Published on Aug 14, 2018


The paper "Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolation" is available here (https://people.cs.umass.edu/~hzjiang//projects/superslomo).

[Airicist]

https://youtu.be/OplLXzxxmdA

Robots teaching themselves to see

Published on Sep 9, 2018

[Airicist]

https://youtu.be/VtXRUTukjNU

Using AI to transform the lives of the blind | Anirudh Koul | TEDxSeattle

Published on Jan 23, 2019


Phone apps make everyone’s lives easier, but for members of the blind community, a new seeing AI app transforms how they live and work every day. Anirudh Koul believes that any disability is merely a gap between what we want to do and what we can do, and it’s technology’s role to fill those gaps. Koul points out that we all experience gaps as we age, and his invention gives all hope for a more empowered future. Growing up in India, Anirudh Kuhl was programming computers at a young age and by high school he was captivated by patterns in data—a key component of artificial intelligence. He moved to the United States to study at Carnegie Mellon and after stints at Yahoo and Microsoft, is now an AI researcher with multiple patents. Driven by his desire to help a dear family member, he took on a hackathon challenge at Microsoft and led development of an app that is now helping hundreds of millions of people with disabilities. It literally puts the gift of sight in their hands. This talk was given at a TEDx event using the TED conference format but independently organized by a local community.

[Airicist2]

"Phenaki (https://phenaki.github.io)"
A model for generating videos from text, with prompts that can change over time, and videos that can be as long as multiple minutes.

Ruben Villegas, Mohammad Babaeizadeh, Pieter-Jan Kindermans, Hernan Moraldo, Han Zhang, Mohammad Taghi Saffar, Santiago Castro, Julius Kunze, Dumitru Erhan