We present methods for training high quality object detectors
very quickly. The core contribution is a pair of fast
training algorithms for piece-wise linear classifiers, which
...
We present a discriminative Hough transform based ob-
ject detector where each local part casts a weighted vote for
the possible locations of the object center. We show that the
...
Subhransu Maji (University of California, Berkeley...
We address the problem of label assignment in computer
vision: given a novel 3-D or 2-D scene, we wish to assign a
unique label to every site (voxel, pixel, superpixel, etc.). To...
Daniel Munoz, James A. Bagnell, Martial Hebert, Ni...
We study the problem of learning to rank images for image retrieval. For a noisy set of images indexed or tagged by the same keyword, we learn a ranking model from some training e...
This paper focuses on the problem of person detection in harsh industrial environments. Different image regions often have different requirements for the person to be detected. Ad...