The computer aided diagnosis (CAD) problems of detecting
potentially diseased structures from medical images are
typically distinguished by the following challenging characterist...
We introduce a text-based image feature and demon-
strate that it consistently improves performance on hard
object classification problems. The feature is built using
an auxilia...
Cross-domain learning methods have shown promising
results by leveraging labeled patterns from auxiliary domains
to learn a robust classifier for target domain, which
has a limi...
Dong Xu, Ivor Wai-Hung Tsang, Lixin Duan, Stephen ...
Most state-of-the-art nonrigid shape recovery methods
usually use explicit deformable mesh models to regularize
surface deformation and constrain the search space. These
triangu...
In this paper, we focus on the problem of detecting/
matching a query object in a given image. We propose a
new algorithm, shape band, which models an object within
a bandwidth ...
Xiang Bai (Huazhong University of Science and Tec...
This paper studies a framework for matching an unknown
number of corresponding structures in two images
(shapes), motivated by detecting objects in cluttered background
and lear...
We present an algorithm for clustering sets of detected
interest points into groups that correspond to visually dis-
tinct structure. Through the use of a suitable colour and tex...
Interactive image segmentation traditionally involves the
use of algorithms such as Graph Cuts or Random Walker.
Common concerns with using Graph Cuts are metrication
artifacts ...
This paper presents an empirical evaluation of the role of
context in a contemporary, challenging object detection task
– the PASCAL VOC 2008. Previous experiments with context...
Alexei A. Efros, Derek Hoiem, James Hays, Martial ...
To recognize three-dimensional objects it is important to
model how their appearances can change due to changes
in viewpoint. A key aspect of this involves understanding
which o...
Ronen Basri, Pedro F. Felzenszwalb, Ross B. Girshi...