algorithm

In a breakthrough that seems more science fiction than science fact, researchers at MIT have developed a model that can recover "lost dimensions" in images. Translation: it can recreate video from a motion-blurred photograph, and may some day be able to create a 3D scan from a 2D image.

The rise of social media has had a massive impact on the art we see, consume, and interact with on a daily basis. Some of that impact was positive, some negative, but one of the most radical changes has also been one of the most detrimental: the demise of the gatekeepers.

There has been a viral "chain letter" type of post that has been spreading on Instagram that warns users of the social network limiting post reach. Instagram has officially responded by saying that it does not do anything to prevent posts from showing up to all your followers.

Instagram experience major user backlash after it abandoned its reverse chronological feed back in 2016, and many users these days are still wishing for its return. If you're one of them, here's an interesting factoid that may change your mind: the chronological feed was making users miss 50% of their friends' posts.

Facebook has suspended 10 large groups on its service that were being used by hundreds of thousands of people to game Instagram in hopes of making their photos more popular.

The Trophy Camera is an experimental camera powered by artificial intelligence that can only shoot images that it deems to be "award-winning."

Videos are made up of about 24 frames every second, but what would happens if you fed a single photo into a motion prediction algorithm, and asked it to create the next 100,000 frames de novo after that? This video is what happens.

A team of researchers at UC Berkeley have revealed an 'Unpaired Image-to-Image Translation' technique that can do something really interesting: it can turn a painting by Monet into a 'photograph'... also, it can transform horses into zebras and summer into winter.

Google scientists are brewing technology that could one day help you to "enhance!" photos with sharper results than current software on the market. Called RAISR, the system uses machine learning for intelligent upscaling.

Well, you can add "captioning photos" to the list of jobs robots will soon be able to do just as well as humans. After some training, the latest version of Google's "Show and Tell" algorithm can describe the contents of a photo with staggering 94% accuracy.

There are no real images of a black hole, only artist renderings like the one above and that really cool CGI version in the movie Interstellar. But that may change in the coming years thanks to an algorithm recently developed at MIT.

How many photos did you come home with from your last professional shoot? Whether that number is several hundred or several thousand, that's a lot of photos to cull through, and a new Artificial Intelligence software called Picturesqe thinks it can help.

Face swap camera apps are all the rage these days, and Facebook even acquired one this month to get into the game. But the technology is getting more and more creepy: you can now hijack someone else's face in real-time video.

The backlash has begun. A day after Instagram announced that its feed will soon be ordered by a Facebook-style curation algorithm, over 100,000+ people have signed an online petition to "Keep Instagram Chronological."

Microsoft has launched a new camera app for iPhones that's designed to help you take the perfect selfie. It's called Microsoft Selfie, and it uses some of Microsoft's latest technology to auto-tweak snapshots of your face.

The braniacs at MIT have created an algorithm to determine the “memorability” of a photograph. The deep learning-based technology “learned” what makes a photo memorable by evaluating the rankings from 5,000 human volunteers, and even indicates which portions of an image it considers to be memorable with a heatmap depiction. The algorithm is allegedly as good as a human in determining what makes a memorable photograph.

But ranking a photo based purely on aesthetics isn’t necessarily how humans associate photographs. Context matters. Where was I? What was I doing? What is this photo representative of? I decided to test the algorithm against TIME magazine’s top 10 photos of 2015.

Some photographs have the power to burn themselves into our memories for a long time, while others are easily forgettable after they're seen. Scientists are MIT have been researching the science behind memorable images, and now they've created a web app called LaMem that can analyze any photo and assign it a memorability score.

Adobe's Content Aware Fill makes it easy to remove distracting elements in photos using Photoshop, but soon you may not have to. Computer vision scientists at Adobe and Princeton are working on a new technology called "distraction prediction" that can automatically find and remove distracting elements from photos.

Scientists have created a new algorithm that can magically give photos the look of famous paintings by old masters.

Researchers at Google and MIT have figured out a way to automatically remove reflections and obstructions from photographs, and their latest demo of the technology is amazing.

Check out the 6.5-minute video above for an explanation of the algorithm and some examples of what it can do.

A new website, IsItNude.com, has set out on a mission to help identify whether or not photographs contain nudity. California-based algorithm company, Algorithmia, designed the custom code for a client, but you can use the above link to test it out for yourself. If interested, you can even pay to use the system within your own application or website.

Time-lapses are usually created with one or more cameras by one or more photographers working together to document a particular subject, but now scientists have created a new method of time-lapse creation that uses photographs found on the Internet.

Photographers often use products such as the Lens Skirt when shooting through windows in order to reduce or remove reflections. Thanks to advances in computer algorithms, those physical tricks may soon find themselves alongside suitable software solutions.

Scientists at MIT have created an algorithm that can automatically remove reflections from photos that were taken through windows.

Could machines be trained to tell the difference between a beautiful portrait photo and a not-so-pleasing one? Beauty is pretty subjective, but scientists are trying to boil down the common properties of beautiful digital portrait photos so that a computer can be trained to spot them. Along the way, they're revealing interesting new things about what people look for in portraits.

Impossible image enhancing is a well-known cliche in movies and TV shows. When law enforcement computer whizzes get their hands on a photograph or video still frame, anything seems to be possible.

It seems a movie finally got image enhancing right. The 36-second clip above is from the 2014 movie Algorithm, a movie that's (fittingly) about a freelance computer hacker who discovers a shady government program.

At the Adobe MAX 2014 conference this past week, Adobe showed off some of the crazy technology current brewing in the company's labs. Two of them offer a glimpse at what may soon be available to photographers in Photoshop: changing the time of day (i.e. lighting) in photographs with a simple slider and removing haze from a scene automatically.

Researchers at Brown University have created an intriguing little algorithm that allows you to alter the weather, time of day and even season in your outdoor photographs.

A photographer's primary concern when taking a photo might not be "I wonder how many likes this will get," but being able to gauge popularity could still come in handy when you're trying to decide which photos to upload to your favorite sharing site.

Enter MIT PhD candidate Aditya Khosla and his new algorithm that does just that: tells you how popular your photos will be before you even upload them.

For you and me, RGB color spaces may just be an obscure but important mechanism towards achieving properly color-balanced photos. For a certain group of image nerds, however, it's the whole enchilada.

As post-production software continues to become more and more powerful, researchers are doing their best to keep up by developing new methods of spotting digital photo fakes. In the past, we've seen that noise patterns and even Twitter trends can help spot fakes, but a new method out of UC Berkeley is taking a look at something else entirely: the shadows.