Computer Vision
Enabling computers and devices to understand what they see.
Video
Inside look at the DARPA Subterranean Urban Circuit Challenge 2020
Over the last year, ten teams from around the world have been participating in the DARPA Subterranean challenges. These challenges are designed to test drones and robots on how they perform in hazardous physical environments…
Video
Learning Visuomotor Policies for Aerial Navigation Using Cross-Modal Representations
Machines are a long way from robustly solving open-world perception-control tasks, such as first-person view (FPV) aerial navigation. While recent advances in end-to-end Machine Learning, especially Imitation and Reinforcement Learning appear promising, they are constrained…
Project
Project Tokyo
Project Tokyo aims to understand how to create a visual agent technology that is both useful and usable in the real world by focusing on how AI technology can help to augment people’s own capabilities.
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…