/udn_extend

pedestrian detection on Caltech dataset
  1. Matlab 86.6%
  2. C++ 7.5%
  3. Cuda 5.4%
  4. Shell 0.5%
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bin
experiments
external/caffe_new
final
functions
imdb/cache
utils
README.md
rcnn_build.m
rpn_0_2.mat
startup.m

README.md

udn_extend

pedestrian detection on Caltech dataset

  1. This model can achieve 9.7% miss rate on refined Caltech reasonable test sets.

Perparation in advance:

  1. download the test images(Caltech test sets, 4024 frames).

The testing step:

  1. download model and prototxt from baidu cloud disk.

  2. unzip the zip file in the root directory.

  3. run experiments/script_rpn_rcnn_new.m

If you have some problems to run this code, please contact ZHOU Hui(smarthuizhou@gmail.com).