Computers That Learn to Imagine Short Video Clips
This new approach teaches a computer to guess what comes next in a video by watching only the footage, no labels or tags needed.
The system learns to predict missing pieces and to fill in or extend short clips, so it starts to notice simple shapes and how they move.
By practicing on many examples, the model begins to spot patterns in time and space, and it can copy those patterns back to the video it sees.
After training on real life clips the machine can produce small, believable movements, not just blur.
It was train on lots of short scenes, and then it can imagine where objects will go a few frames ahead.
This work shows machines can learn from raw footage and capture motion and change, and even guess missing frames in a short clip of natural videos.
The result is simple but exciting — a step toward tools that watch, learn, and help make new video ideas, maybe sooner than you think.
Read article comprehensive review in Paperium.net:
Video (language) modeling: a baseline for generative models of natural videos
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