Computer vision
Teaching machines to interpret and reason about the visual world, from object recognition to medical imaging.
Video
Research talks: Learning for interpretability
Speakers: Hanwang Zhang, Professor, Nanyang Technological University Yuwang Wang, Senior Researcher, Microsoft Research Asia Shujian Yu, Professor, UiT – The Arctic University of Norway One of the critical shortcomings of big data-driven deep learning is…
Video
Keynote: Learning from observation: Small-data approach to human common sense
Speaker: Katsushi Ikeuchi, Sr. Principal Research Manager, Microsoft Research Redmond Learning-from-Observation (LfO), a robot-teaching paradigm, aims to build a robot system that understands what humans do through a small number of human observations and map…
Video
Research talks: Few-shot and zero-shot visual learning and reasoning
Humans learn, infer, and reason by leveraging prior knowledge without necessarily observing a large number of examples. Visual learning and reasoning technologies, such as few-shot and zero-shot learning, aim to enable human-like learning and reasoning…
Group
Biomedical Imaging
We are exploring how novel signal processing techniques and AI can allow us to produce images from less data than is currently required.
Microsoft Research Blog
ACAV100M: Scaling up self-supervised audio-visual learning with automatically curated internet videos
The natural association between visual observations and their corresponding sounds has exhibited powerful self-supervision signals for learning video representations, which makes the ever-growing amount of online video an attractive data source for self-supervised learning. However,…
Project
SmartKC: A Smartphone-based Corneal Topographer
Keratoconus is a severe eye disease affecting the cornea (the clear, dome-shaped outer surface of the eye), causing it to become thin and develop a conical bulge. If not treated in time, keratoconus can lead…