RI Seminar
Kristen Grauman
Clare Boothe Luce Assistant Professor, Department of Computer Science
University of Texas at Austin

Steering Human Insight for Large-Scale Visual Learning

Event Location: 1305 Newell Simon HallBio: Kristen Grauman is a Clare Boothe Luce Assistant Professor in the Department of Computer Science at the University of Texas at Austin. Her research in computer vision and machine learning focuses on visual search and object recognition. Before joining UT-Austin in 2007, she received her Ph.D. in the EECS [...]

RI Seminar
James O'Brien
Associate Professor, Computer Science
UC Berkeley

Sparse Matrix Factorization, Mesh Modification, and Real-Time FEM Simulation

Event Location: 1305 Newell Simon HallBio: James F. O'Brien is an Associate Professor of Computer Science at the University of California, Berkeley. His primary area of interest is Computer Animation, with an emphasis on generating realistic motion using physically based simulation and motion capture techniques. He has authored numerous papers on these topics. In addition [...]

Seminar
William Swartout
Director of Technology Institute for Creative Technologies and Research Associate Professor of Computer Science
University of Southern California

What Have We Learned From Virtual Humans?

Event Location: Rashid Auditorium - Gates and Hillman Centers 4401. Open to the public.Bio: William Swartout is Director of Technology for USC's Institute for Creative Technologies (ICT) and a research professor of computer science at USC. His particular research interests include virtual humans, explanation and text generation, knowledge acquisition, knowledge representation, intelligent computer based education, [...]

RI Seminar
Pyry Matikainen
Carnegie Mellon University

Generating Representations for Action Recognition From Coarsely Labeled and Synthetic Data

Event Location: NSH 1507Abstract: Action recognition techniques rely heavily on well chosen features, such as trajectory-based motion descriptors, to make the most of relatively scarce video training data. Typically these features must be hand-selected because the very paucity of suitably annotated data that makes the selection of features critical also restricts the degree to which [...]