News Releases from 2016
November 30, 2016
Becoming a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) is the organization’s ultimate status for top electrical engineers, computer engineers and computer scientists. This week, IEEE announced its list of newly-elevated Fellows for 2017, including two members of the Center for Visual Computing (VisComp).
September 27, 2016
Center for Visual Computing Faculty and Students to Present 8 papers at the European Conference on Computer Vision
Faculty and students from the Center for Visual Computing will present eight papers at ECCV, the European Conference on Computer Vision, Oct. 8-16, 2016 the premier international forum for computer vision research this year, held in Amsterdam.
July 21, 2016
Iron Man’s suit. Captain America’s shield. The Batmobile. These all could look a lot more realistic thanks to a new algorithm developed by a team of U.S. computer graphics experts. The researchers, led by Professor Ravi Ramamoorthi at the University of California San Diego, have created a method to improve how computer graphics software reproduces the way light interacts with extremely small details, called glints, on the surface of a wide range of materials, including metallic car paints, metal finishes for electronics and injection-molded plastic finishes.
July 5, 2016
Ravi Ramamoorthi, a computer science professor at the University of California San Diego, is one of 11 finalists for the inaugural edX Prize for Exceptional Contributions in Online Teaching and Learning.
June 9, 2016
University of California San Diego professor Ravi Ramamoorthi is the inaugural holder of a new endowed faculty chair in the university’s Department of Computer Science and Engineering (CSE).
February 19, 2016
Google has selected computer scientist Ravi Ramamoorthi, director of UC San Diego's Center for Visual Computing, to receive one of its Faculty Research Awards in 2016. It is Ramamoorthi's second such award, after receiving one in 2014 while he was still at UC Berkeley (just months before he joined the Department of Computer Science and Engineering at UC San Diego).
February 8, 2016
What if computers could recognize objects as well as the human brain could? Electrical engineers at the University of California, San Diego have taken an important step toward that goal by developing a pedestrian detection system that performs in near real-time (2–4 frames per second) and with higher accuracy (close to half the error) compared to existing systems. The technology, which incorporates deep learning models, could be used in “smart” vehicles, robotics and image and video search systems.