Computer vision
Teaching machines to interpret and reason about the visual world, from object recognition to medical imaging.
Group
Deep Learning Group
The Deep Learning group advances the state-of-the-art in deep learning to achieve general intelligence. We develop algorithms, models, and systems in deep supervised and unsupervised learning, deep reinforcement learning, and neural-symbolic reasoning, and then pursue breakthroughs in computer vision,…
Tool
Gait and Balance App
The Gait and Balance app uses the Kinect for Windows (V2) to measure different metrics related to gait and balance. This can be used, for example, for assessing risk of fall among older adults or…
Video
Faculty Summit 2016: Hot Topics
Generating Natural Questions About an Image CryptoNets: Machine Learning Inference on Encrypted Data Everest: Deploying Verified-Secure Implementations in the HTTPS Ecosystem Molecular Programming
Project
Image Accessibility
Digital imagery pervades modern life. More than a billion images per day are produced and uploaded to social media sites, and we also encounter digital images within websites, apps, digital documents, and eBooks. Engaging with…
Group
Intelligent Multimedia Group
The Intelligent Multimedia (IM) group aims to build seamless yet efficient multimedia applications and services through breakthroughs in fundamental theory and innovations in algorithm and system technology. We address the problems of intelligent multimedia content…
Tool
SeeingVR Toolkit
Current virtual reality applications do not support people who have low vision, i.e., vision loss that falls short of complete blindness but is not correctable by glasses. We present SeeingVR, a set of 14 tools…
Video
First-person Perception and Interaction
MSR Distinguished Lecture Series: First-person Perception and Interaction Computer vision has seen major success in learning to recognize objects from massive “disembodied” Web photo collections labeled by human annotators. Yet cognitive science tells us that…
