
This is supplemental material to CVPR 2013 Paper #1025

Histograms of Sparse Codes for Object Detection
Xiaofeng Ren, Deva Ramanan

It includes two folders:

(1) ./prs

This folder contains the precision-recall curves for the 20 PASCAL2007 classes,
using our system to compare Histograms-of-Sparse Codes (HSC) vs standard HOG
features under identical settings. The HSC features consistently outperform HOG
in all cases, in particular in mid/high-recall regime (see text for detail).

As a reference, we also include results from the publicly available
voc-release4 system [14]. The precision-recall curves are obtained from
(re-)training models using their system as is. The average precision numbers
are slightly lower than reported on the authors' website, mainly because we are
not using the bounding box re-prediction for any of the experiments.

(2) ./examples, with 2 subfolders ./rootonly and ./parts

This folder contains comparison examples of HSC-based vs HOG-based detection
for a number of PASCAL2007 classes. For the root-only case, we show top 3
candidates, in the order of red, green, blue.  For the part-based case, we show
the top candidate with parts. We do much better on challenging cases with
complex appearances and weak contours.

For more information, please visit

http://homes.cs.washington.edu/~xren/research/cvpr2013_detection/


