AI Technology & Industry Review
Google AI researchers developed a sign language detection model for video conferencing applications that can perform real-time identification of a person signing as an active speaker.
A Stanford University research team has responded with an AI-powered model capable of realistically simulating a Wimbledon final and more.
In the seminal 1996 paper Light Field Rendering, Levoy and Hanrahan describe a representation for light fields that allows for both efficient creation and display.
Researchers from the University of Washington, Virginia Tech and Facebook have introduced an algorithm that can reconstruct dense, geometrically consistent depth for all pixels in monocular videos.
Synced has selected 10 AI-oriented YouTube channels we hope might provide our readers a cozy little holiday binge-watching session.
Researchers from the University of Tsukuba and Waseda University in Japan recently introduced a single framework designed to tackle an entire range of remastering tasks for films that have been converted to digital data.
Researchers from MIT Media Lab and Adobe Research recently introduced a real-time interactive augmented video system that enables presenters to use their bodies as storytelling tools by linking gestures to illustrative virtual graphic elements.
Have you ever shot a perfect video only to have it spoiled by an unsightly pedestrian, truck or other moving object passing through the frame? Although most people know how to crop or photoshop their photos to remove unwanted stuff, doing so with video is another matter entirely.
NVIDIA researchers have developed a deep learning-based system which can produce high-quality slow-motion video from a standard (30 fps) video clip. In comparison with manual slow motion results, the NVIDIA demonstration video shows far superior smoothness.