Method

lapulasi weight loss attention [LWLANet]
none

Submitted on 21 Jun. 2023 04:28 by
家艺 于 (江南大学)

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

Method Description:
use lapulasi uncertanted weight loss
Parameters:
alpha=0.2
Latex Bibtex:
none

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) 94.22 % 91.12 % 81.22 %
Car (Orientation) 94.16 % 90.79 % 80.74 %
Car (3D Detection) 26.74 % 16.67 % 14.33 %
Car (Bird's Eye View) 34.73 % 22.84 % 19.52 %
This table as LaTeX

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



Orientation estimation results.
This figure as: png eps txt gnuplot



3D object detection results.
This figure as: png eps txt gnuplot



Bird's eye view results.
This figure as: png eps txt gnuplot




eXTReMe Tracker