Method

RetinaNet4Kitti [retinanetkitti]
[Anonymous Submission]

Submitted on 4 Sep. 2018 17:21 by
[Anonymous Submission]

Running time:1.5 s
Environment:1 core @ 2.5 Ghz (Python)

Method Description:
Train RetinaNet with pre-trained resnet50 model
Parameters:
input size;224x224
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
Car (Detection) 85.90 % 79.18 % 70.04 %
Pedestrian (Detection) 82.94 % 73.40 % 69.04 %
Cyclist (Detection) 77.60 % 64.44 % 57.66 %
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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