Teaching computers to understand the visual world
We want to change the way you interact with visual data. We want to make your photos magical, we want to deeply understand images and videos from cameras everywhere: in your phone, on your Xbox, in your fridge, on robots, in cars, anywhere. We want you to be able to find your stuff, answer questions, make fantastic new images. And we do that by inventing new algorithms and thinking of new mathematical models for how images come to be.
C. Morrison, K. Huckvale, B. Corish, J. Dorn, P. Kontschieder, K. O'Hara, ASSESS MS Team, A. Criminisi, and A. Sellen, Assessing Multiple Sclerosis with Kinect: Designing Computer Vision Systems for Real-World Use, in Human-Computer Interaction, January 2016.
Simon Korman, Eyal Ofek, and Shay Avidan, Peeking Template Matching for Depth Extension, in The International Conference on Computer Vision 2015, IEEE – Institute of Electrical and Electronics Engineers, 13 December 2015.
James Steven Supančič III, Grégory Rogez, Yi Yang, Jamie Shotton, and Deva Ramanan, Depth-based hand pose estimation: data, methods, and challenges, in Proc. ICCV, IEEE – Institute of Electrical and Electronics Engineers, December 2015.
Danhang Tang, Jonathan Taylor, Pushmeet Kohli, Cem Keskin, Tae-Kyun Kim, and Jamie Shotton, Opening the Black Box: Hierarchical Sampling Optimization for Estimating Human Hand Pose, in Proc. ICCV, IEEE – Institute of Electrical and Electronics Engineers, December 2015.
S. Blessenohl, C. Morrison, A. Criminisi, and J. Shotton, Improving Indoor Mobility of the Visually Impaired with Depth-Based Spatial Sound, in ICCV-ACVR workshop, December 2015.
Join us! Do you love to turn mathematics into code? Do you want to build the future? Then Apply here.
- Peeking Template Matching for Depth Extension
- SemanticPaint: Interactive 3D Labeling and Learning at your Fingertips
- RoomAlive Toolkit
- Depth from Time-of-Flight
- From Captions to Visual Concepts and Back
- Presenter Camera
- Eye Gaze Keyboard
- Human activity detection in RGBD videos
- Fully Articulated Hand Tracking
Our research page.