Establishing visual correspondences is an essential component
of many computer vision problems, and is often done
with robust, local feature-descriptors. Transmission and
storag...
In this paper, we address the problem of learning an
adaptive appearance model for object tracking. In particular,
a class of tracking techniques called “tracking by detection...
We present a method for the detection of instances of an
object class, such as cars or pedestrians, in natural images.
Similarly to some previous works, this is accomplished via
...
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 ...
Non-rigid object detection and articulated pose estimation
are two related and challenging problems in computer
vision. Numerous models have been proposed over the
years and oft...
Mykhaylo Andriluka (TU Darmstadt), Stefan Roth (TU...
In recent years, 3D deformable surface reconstruction
from single images has attracted renewed interest. It has
been shown that preventing the surface from either shrinking
or s...
Mathieu Salzmann (University of California, Berkel...
Images of an object undergoing ego- or camera- motion
often appear to be scaled, rotated, and deformed versions
of each other. To detect and match such distorted patterns
to a s...
We present a new approach to robust pose-variant face
recognition, which exhibits excellent generalization ability
even across completely different datasets due to its weak
depe...
John Wright (University of Illinois), Gang Hua (Mi...
Blind deconvolution is the recovery of a sharp version of
a blurred image when the blur kernel is unknown. Recent
algorithms have afforded dramatic progress, yet many aspects
of...
We propose a novel approach for modelling correlations
between activities in a busy public space captured by multiple
non-overlapping and uncalibrated cameras. In our approach,
...
Chen Change Loy (Queen Mary, University of London)...