Method

Simi-Fusion [Simi-fusion]
[Anonymous Submission]

Submitted on 4 Apr. 2023 10:05 by
[Anonymous Submission]

Running time:0.08 s
Environment:1 core @ 2.5 Ghz (C/C++)

Method Description:
Utilizing attention mechanisms across diverse
abstraction levels, we can effectively identify
similarities between distinct modalities. This
process enables the harmonization of features from
various modalities, bringing them together into a
coherent fusion. By doing so, we facilitate a more
robust and unified representation of the input
data. The approach ensures a seamless integration
of multimodal information, ultimately enhancing
the overall performance of the system.
Parameters:
batch_size=4
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) 98.35 % 95.38 % 92.87 %
Car (Orientation) 98.27 % 95.17 % 92.58 %
Car (3D Detection) 91.82 % 85.02 % 82.43 %
Car (Bird's Eye View) 95.45 % 91.64 % 89.13 %
This table as LaTeX

2D object detection results.
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Orientation estimation results.
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3D object detection results.
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Bird's eye view results.
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