Researchers have recently developed a deep learning method and a process that has the potential to produce a seamlessly looping, realistic-looking video from a single picture. Photographs show us the sill moment that does not capture the scene truly sometimes, but with the video, we could be able to see the movement in the scene. Imagine a scene of Kaieteur falls with a still picture. There is no moment of joy as the water is not moving. So researchers from the University of Washington have developed a deep learning method through which they procure an endlessly looped video from a single photograph. The system has the ability to show the video of water cascading down from just a picture. They did this by running the photograph in a loop position. Everything is so perfect that you have the feel of water coming downwards by one photo, and it gives us the sense of the actual video is playing. All that is missing is the roar of the water body and water spray on your face.
The team method can animate any flowing material such as smoke and clouds. This technique creates a short video that repeats itself seamlessly and gives the impression of continuous movement. The researchers presented this approach on June 22nd at the Conference on Computer Vision and Pattern Recognition. "An image captures a frozen moment, but a lot of information is lost in a static image," said lead author Aleksander Holynski, a Ph.D. student at the Paul G. Allen School of Engineering and Computer Science. The specialty and uniqueness of our method is that no user input or additional information is required." Said Holynski. All you need is one photograph. And it outputs high-resolution, seamlessly repeating video that often looks like real video. "Developing a method that would turn a single photo into a believable video has been challenging for the industry. Indeed, it requires you to predict the future," said Holynski. in the real world, there are almost infinite possibilities of what could happen next.
