Method

GNN [GNN]


Submitted on 18 Jun. 2017 04:48 by
Gao Pan (Nanchang Hangkong university)

Running time:0.2 s
Environment:1 core @ 2.5 Ghz (Python)

Method Description:
faster rcnn with ohem
Parameters:
resnet101
Latex Bibtex:
TAB

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
Car (Detection) 76.03 % 62.59 % 50.18 %
Pedestrian (Detection) 58.22 % 42.56 % 40.53 %
Cyclist (Detection) 59.43 % 42.65 % 37.72 %
This table as LaTeX


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



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



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




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