Researches in our lab focus on two intimately connected branches of vision research: computer vision and human vision. In both fields, we are intrigued by visual functionalities that give rise to semantically meaningful interpretations of the visual world. In computer vision, we aspire to build intelligent visual algorithms that perform important visual perception tasks such as object recognition, scene categorization, integrative scene understanding, human motion recognition, material recognition, etc. In human vision, our curiosity leads us to study the underlying neural mechanisms that enable the human visual system to perform high level visual tasks with amazing speed and efficiency.

news and events [news archive]
New Dataset!	We just released a new 3D Object Category Dataset based on Savarese & Fei-Fei, ICCV 2007.
New Dataset!	We just released a new Event Dataset, consisting of 8 classes of sport event photos, based on L.-J. Li & L. Fei-Fei, ICCV 2007.
2007.07	Our UIUC-Princeton Team won the 1st Place in the Software League of the AAAI 07 Semantic Robot Vision Challenge! Congratulations to the team members!
2007.07	Congratulations to the 3 papers accepted by ICCV 2007: S. Savarese & L. Fei-Fei (Oral); L.-J. Li & L. Fei-Fei (poster); and L. Cao & L. Fei-Fei (poster).

press coverage
2007.08	News articles related to Team OPTIMOL (UIUC-Princeton) at the Semantic Robot Vision Challange: 1) New Scientist magazine (full article); 2) UIUC ECE Dept. news
2007.06	"Taking the scenic route", companion article of Princeton EQUAD News "Frontiers of Health", School of Engineering and Applied Sciences, Princeton.
2006.05.03	"Recognizing the brightest minds in computer science," Microsoft press release
2006.04.26	"Microsoft Research recognizes computer science's most promising professors with New Faculty Fellowships," Microsoft press release