A multi-class collaborative detection and tracking framework that fuses multi-agent LiDAR and camera features, uses DINOv2 for re-identification, and adapts track lifetimes to object speed.
Multi- view robust collaborative localization in high outlier ratio scenes based on semantic features,
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
-
DINO-CoDT: Multi-class Collaborative Detection and Tracking with Vision Foundation Models
A multi-class collaborative detection and tracking framework that fuses multi-agent LiDAR and camera features, uses DINOv2 for re-identification, and adapts track lifetimes to object speed.