Rope3d: The roadside perception dataset for autonomous driving and monocular 3d object detection task
Concurrent perception datasets for autonomous driving are mainly limited to frontal view
with sensors mounted on the vehicle. None of them is designed for the overlooked roadside …
with sensors mounted on the vehicle. None of them is designed for the overlooked roadside …
Mutr3d: A multi-camera tracking framework via 3d-to-2d queries
Accurate and consistent 3D tracking from multiple cameras is a key component in a vision-
based autonomous driving system. It involves modeling 3D dynamic objects in complex …
based autonomous driving system. It involves modeling 3D dynamic objects in complex …
The devil is in the details: Self-supervised attention for vehicle re-identification
In recent years, the research community has approached the problem of vehicle re-
identification (re-id) with attention-based models, specifically focusing on regions of a …
identification (re-id) with attention-based models, specifically focusing on regions of a …
VehicleNet: Learning robust visual representation for vehicle re-identification
One fundamental challenge of vehicle re-identification (re-id) is to learn robust and
discriminative visual representation, given the significant intra-class vehicle variations …
discriminative visual representation, given the significant intra-class vehicle variations …
Multi-domain learning and identity mining for vehicle re-identification
This paper introduces our solution for the Trcak2 in AI City Challenge 2020 (AICITY20). The
Track2 is a vehicle re-identification (ReID) task with both the real-world data and synthetic …
Track2 is a vehicle re-identification (ReID) task with both the real-world data and synthetic …
Electricity: An efficient multi-camera vehicle tracking system for intelligent city
City-scale multi-camera vehicle tracking is an important task in the intelligent city and traffic
management. It is quite challenging with large scale variance, frequent occlusion and …
management. It is quite challenging with large scale variance, frequent occlusion and …
A robust mtmc tracking system for ai-city challenge 2021
Abstract Multi-Target Multi-Camera tracking (MTMC) is an essential task in the intelligent city
and traffic analysis. It is a great challenging task due to several problems such as heavy …
and traffic analysis. It is a great challenging task due to several problems such as heavy …
Box-grained reranking matching for multi-camera multi-target tracking
Abstract Multi-Camera Multi-Target tracking (MCMT) is an essential task in intelligent
transportation systems. It is highly challenging due to several problems such as heavy …
transportation systems. It is highly challenging due to several problems such as heavy …
Multi-target multi-camera tracking of vehicles using metadata-aided re-id and trajectory-based camera link model
In this paper, we propose a novel framework for multi-target multi-camera tracking (MTMCT)
of vehicles based on metadata-aided re-identification (MA-ReID) and the trajectory-based …
of vehicles based on metadata-aided re-identification (MA-ReID) and the trajectory-based …
Strdan: Synthetic-to-real domain adaptation network for vehicle re-identification
Vehicle re-identification (Re-ID) aims to obtain the same vehicles from vehicle images.
Vehicle Re-ID is challenging but important for analyzing and predicting traffic flow in the city …
Vehicle Re-ID is challenging but important for analyzing and predicting traffic flow in the city …