My research focuses on computer vision, often motivated by the task of understanding people from visual data. My work tends to make heavy use of machine learning techniques, often using the human visual system as inspiration. For example, temporal processing is a key component of human perception, but is still relatively unexploited in current visual recognition systems. Machine learning from big (visual) data allows systems to learn subtle statistical regularities of the visual world. But humans have the ability to learn from very few examples. Here’s a recent talk (from 2015) that discusses some thoughts on these issues.
Mengtian Li, Laszlo Jeni and Deva Kannan Ramanan
Conference Paper, AAAI 2018, February, 2018
Yuxiong Wang, Deva Kannan Ramanan and Martial Hebert
Conference Paper, 31st Conference on Neural Information Processing Systems (NIPS), December, 2017
Yuxiong Wang, Deva Ramanan and Martial Hebert
Conference Paper, IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), July, 2017