A two-stage YOLOv5 + CUT + EfficientNet pipeline for vehicle class and orientation detection improves weighted mAP from 0.284 to 0.365 on the IEEE BigData 2022 VOD test set.
Citywide recon- struction of cross-sectional traffic flow from moving camera videos,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.CV 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
A 2-Stage Model for Vehicle Class and Orientation Detection with Photo-Realistic Image Generation
A two-stage YOLOv5 + CUT + EfficientNet pipeline for vehicle class and orientation detection improves weighted mAP from 0.284 to 0.365 on the IEEE BigData 2022 VOD test set.