Skip to content

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

8 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Adaptive Feature Attention Fusion Network for Lane Detection in Foggy Conditions

The paper code will be released soon...

Structure

Fig1

Datasets

Benchmark

Comparison on the FogTuSimple dataset with other methods, where ’-’ repre-

sents unavailable values

Method ACC F1 FP FN FPS
SCNN 94.31% 90.95% 0.0619 0.0729 30
LaneNet 93.75% 93.7% 0.0821 0.0312 41
Enet-SAD 95.23% 94.42% 0.0681 0.0225 33
UFLD 94.04% - 0.2157 0.0703 98
Ours 94.62% 91.17% 0.0613 0.0687 43

Comparison with other methods on the FogCULane dataset and the original CULane dataset, the values in the table represent the F1 measurement for each scene

Category Enet-SAD (CULane) Enet-SAD (Fog) SCNN (CULane) SCNN (Fog) UFLD (CULane) UFLD (Fog) Ours (CULane) Ours (Fog)
Normal 90.1% 88.6% 90.6% 83.63% 87.7% 87.72% 77.57% 82.63%
Crowded 68.8% 65.9% 69.7% 69.63% 66.0% 65.12% 56.37% 61.44%
Night 66.0% 64.3% 66.1% 66.10% 61.8% 62.14% 54.09% 58.89%
No-line 41.6% 38.7% 43.4% 37.66% 40.2% 35.84% 31.39% 35.48%
Shadow 62.7% 66.9% 49.0% 49.02% 58.3% 58.36% 44.54% 50.31%
Arrow 84.0% 79.5% 84.1% 72.95% 81.8% 81.85% 65.62% 73.07%
Dazzle 60.2% 58.2% 58.5% 55.17% 58.4% 52.47% 49.68% 53.53%
Curve 68.8% 65.1% 64.4% 57.22% 57.9% 57.96% 51.86% 57.07%
Average 70.8% 68.62% 71.6% 64.07% 68.4% 67.07% 58.69% 65.45%

About

This is the code of paper "Enhanced Lane Detection in Foggy Conditions via Adaptive Feature Attention Fusion Network"

Resources

Stars

1 star

Watchers

1 watching

Forks

Releases

Packages

Used by

Contributors

Languages