Method

Fast-RCNN on different Selective search configurations [Fast-RCNN-SS]
[Anonymous Submission]

Submitted on 24 Feb. 2016 12:15 by
[Anonymous Submission]

Running time:1 s
Environment:GPU @ 2.0 Ghz (Matlab + C/C++)

Method Description:
Used Fast-RCNN and trained with Kitti training samples over ImageNet model.
Parameters:
The boxes has been generated using Selective search on non-fast mode.
Latex Bibtex:

Detailed Results

Object detection and orientation estimation results. Results for object detection are given in terms of average precision (AP) and results for joint object detection and orientation estimation are provided in terms of average orientation similarity (AOS).


Benchmark Easy Moderate Hard
Pedestrian (Detection) 54.20 % 41.59 % 35.26 %
This table as LaTeX


2D object detection results.
This figure as: png eps pdf txt gnuplot




eXTReMe Tracker