A two-module post-processing framework (tracking-based relabeling plus virtual bounding box injection) reports +1.6% to +3.1% mAP@50 on helmet violation detection, but only on a self-annotated test set with fitted confidence offsets.
Yolo-v1 to yolo-v8, the rise of yolo and its complementary nature toward digital manufacturing and industrial defect detection,
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
REJECT 1roles
background 1polarities
support 1representative citing papers
citing papers explorer
-
VisionGuard: Synergistic Framework for Helmet Violation Detection
A two-module post-processing framework (tracking-based relabeling plus virtual bounding box injection) reports +1.6% to +3.1% mAP@50 on helmet violation detection, but only on a self-annotated test set with fitted confidence offsets.