Method

Localized Semantic Feature Mixers [at] [LSFM]
[Anonymous Submission]

Submitted on 14 Oct. 2023 20:13 by
[Anonymous Submission]

Running time:0.05 s
Environment:4 cores @ 2.5 Ghz (Python)

Method Description:
MLP-Mixer based novel architecture for motion blur robust object detection model. Utilizes SP3 a novel object detection neck to efficiently enrich and filter high level semantic features. Uses Dense Focal Detection Network to efficiently detect objects in center and scale fashion.
Parameters:
learning_rate = 0.0002
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) 86.81 % 81.26 % 77.64 %
Pedestrian (Orientation) 48.58 % 44.92 % 42.74 %
This table as LaTeX

2D object detection results.
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Orientation estimation results.
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