Method

Dual-domain Deformable Feature Fusion [DDF]
[Anonymous Submission]

Submitted on 28 Apr. 2024 08:05 by
[Anonymous Submission]

Running time:0.1 s
Environment:1 core @ 2.5 Ghz (Python)

Method Description:
We propose a dual-domain deformable feature fusion network for 3D
object detection. It not only pays attention to more context
information in voxel and image features, but also adaptively pays
attention to different details in the image domain in each layer,
further improving the accuracy of feature alignment and fusion
performance.
Parameters:
NAN
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) 96.53 % 95.83 % 93.25 %
Car (Orientation) 96.52 % 95.78 % 93.17 %
Car (3D Detection) 89.69 % 82.03 % 79.47 %
Car (Bird's Eye View) 92.57 % 89.00 % 86.50 %
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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