Software & Technology

The Future of AI Imaging – Artsy

Sometime in the not-too-distant future, anyone will be able to take a picture without a camera. Instead, we will be able to generate photographs, indistinguishable from those made by a camera, using artificial intelligence (AI) software. You will be able to create an image by simply typing out a description of the scene, or describing it to (presumably) Siri. “Siri,” you’ll say. “I’d like an image of a red-haired woman walking through a park in autumn, the breeze blowing red, orange, and yellow leaves around her.” And—though it may require more detail than that—presto! Your phone will provide various options on the screen to choose from.

Pro Photographers Should Pay Attention to the Google Pixel 3 – PhotoShelter Blog

Google has officially launched its incredible “Night Sight” feature on the Pixel 3 camera app. Computational photography pioneer and Google Distinguished Engineer Marc Levoy co-wrote a blog describing all the different considerations that went into developing the jaw dropping technology that allows the Pixel to see in the dark. It’s worth a read.

NY Times Using Google AI to Digitize 5M+ Photos and Find ‘Untold Stories’

The New York Times has teamed up with Google Cloud for digitizing five to seven million old photos in its archive. Google’s AI will also be tasked with unearthing “untold stories” in the massive trove of historical images.

How the BBC verified that video of a grisly murder in Cameroon, step-by-step | Poynter

So the BBC started looking into the video, which allegedly took place in Cameroon. In July, when the video first went viral, the government there dismissed the allegations as “fake news” on the basis that the soldiers depicted were not wearing the right gear or carrying the right weapons.

New study analyzes what’s driving the explosion in user-generated videos and hybrid photo-videos – Kaptur

Consumer video sure ain’t what it used to be. The category now includes numerous variations, ranging from full-length to short-form narratives, plus what could be called “phodeos”: hybrids of photos and videos such as Boomerang clips, Instagram Stories, and even the (now venerable) GIF animations. Due in large part to these new options that free consumers from the “one (huge) size fits all” straightjacket of the past, motion imaging is more popular now than ever.

AVA: The Art and Science of Image Discovery at Netflix

At Netflix, the Content Platform Engineering and Global Product Creative teams know that imagery plays an incredibly important role in how viewers find new shows and movies to watch. We take pride in surfacing the unique elements of a story that connect our audiences to diverse characters and story lines. As our Original content slate continues to expand, our technical experts are tasked with finding new ways to scale our resources and alleviate our creatives from the tedious and ever-increasing demands of digital merchandising. One of the ways in which we do this is by harvesting static image frames directly from our source videos to provide a more flexible source of raw artwork.

Technical Camera: An iOS Camera App with a Simple UI and Serious Features

The Hungarian software company DIRE Studio has just launched Technical Camera, a new iOS camera app that’s designed for serious photographers who want a simple yet advanced tool for capturing still photos.

What you missed at the 2018 LDV Vision Summit – Kaptur

The 2018 edition of the LDV Vision Summit was, like its four predecessors, a refreshing display of creative ingenuity, stunning engineering and brilliant problem-solving. With successive keynotes never longer than 5 minutes each, subtlety interrupted by more extended fire chats or panels, there is no room for boredom. Even if a topic or speaker might not be in your field of interest, it is not long before another will keep you glued to your chair and wanting to know more. Which, thanks to the casual and friendly networking, is not hard to do. Speakers are all available to explain more if needed and do business, if appropriate. No superstars here leaving in limos the minute they step out the stage. Instead, a succession of people passionate about their work as much as the audience.

See in the Dark: a machine learning technique for producing astoundingly sharp photos in very low light / Boing Boing

A group of scientists from Intel and the University of Illinois at Urbana–Champaign have published a paper called Learning to See in the Dark detailing a powerful machine-learning based image processing technique that allows regular cameras to take super-sharp pictures in very low light, without long exposures or the kinds of graininess associated with low-light photography.

Facebook Training Image Recognition AI with Billions of Instagram Photos

While companies and researchers around the world work to build the most advanced and powerful AI systems, Facebook has a special treasure trove that most don’t: billions of tagged photos thanks to Instagram. Facebook has now used those photos to create a leading image recognition AI.

Canon’s New Speedlite 470EX-AI Shows How Fast Computational Photography Is Moving – PhotoShelter Blog

We previously wrote about the state of computational photography in September 2017. Included within that piece was a reference to the work by Kukas Murmann, Abe Davis, Jan Kautz and Frédo Durand who built a prototype flash mounted on a servo and connected to an electric eye. The mechanism provided an automated way to position a flash to provide indirect light. The resulting images were a dramatic step up from direct flash photography.

10 Questions for a Founder : TruePic – Kaptur

With each iteration of Photoshop, it is easier and easier to alter images, making it impossible to spot the alterations. Soon, with AI generated images taking over in many fields, it will be impossible to trust if an image is an actual photograph or a complete fabrication. Photography is in danger of losing its essential tie to reality and truth. Enters TruePic. With an array of patented technologies, the company offers a solid counterbalance to this seemingly unstoppable wave of reality-altering technologies. It certifies that a photograph is 100% original and has not been tampered with. We spoke with CEO Jeff McGregor to learn more:

OK Computer: Computational photography is here to stay!

Whilst many photographers remain deep in conversation concerning the evolution from analog to digital photography—and the positives and negatives of both—the world of photographic technology has paid little heed to their protestations and continued on with its research and development. As a result, we find ourselves today — in fact we have been here for some time — in the age of computational photography.

2 research that will change photography forever – Kaptur

A couple of research papers were recently published, both touching on advancement in computer vision and machine learning. While research papers are a common occurrence in this field, these two are worth reviewing a bit deeper, as their implication will have a wide impact once they mature.

A crypto Kodak mess ? – Thoughts of a Bohemian

Will stop here with our analysis because it seems to be clear that even if it is under the once respected name of Kodak, this project still has a lot to clear before becoming trustable. For one, and foremost, a working demo would go a long way to demonstrate exactly how this functions and if viable. As well, it would eliminate any doubts that this is not a get quick rich tech play that might leave a lot of photographers worst than where they are now.

How an A.I. ‘Cat-and-Mouse Game’ Generates Believable Fake Photos – The New York Times

At a lab in Finland, a small team of Nvidia researchers recently built a system that can analyze thousands of (real) celebrity snapshots, recognize common patterns, and create new images that look much the same — but are still a little different. The system can also generate realistic images of horses, buses, bicycles, plants and many other common objects.

How Do You Vote? 50 Million Google Images Give a Clue – The New York Times

For the first time, helped by recent advances in artificial intelligence, researchers are able to analyze large quantities of images, pulling out data that can be sorted and mined to predict things like income, political leanings and buying habits. In the Stanford study, computers collected details about cars in the millions of images it processed, including makes and models.

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