In this paper, we present a systematic framework for re-cognizing realistic actions from videos “in the wild.” Such unconstrained videos are abundant in personal collections as...
Jingen Liu (University of Central Florida), Jiebo ...
This paper proposes a novel approach to motion capture
from multiple, synchronized video streams, specifically
aimed at recording dense and accurate models of the structure
and ...
Yasutaka Furukawa (University of Washington), Jean...
Restoring a clear image from a single motion-blurred
image due to camera shake has long been a challenging
problem in digital imaging. Existing blind deblurring techniques
eithe...
Jian-Feng Cai (National University of Singapore), ...
Current work in object categorization discriminates
among objects that typically possess gross differences
which are readily apparent. However, many applications
require making ...
Andrew Moldenke, Asako Yamamuro, David A. Lytle, E...
Multi-instance multi-label learning (MIML) refers to the
learning problems where each example is represented by a
bag/collection of instances and is labeled by multiple labels.
...
Rong Jin (Michigan State University), Shijun Wang...