Vehicle Re-Identification
53 papers with code • 12 benchmarks • 9 datasets
Vehicle re-identification is the task of identifying the same vehicle across multiple cameras.
( Image credit: A Two-Stream Siamese Neural Network for Vehicle Re-Identification by Using Non-Overlapping Cameras )
Benchmarks
These leaderboards are used to track progress in Vehicle Re-Identification
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
Libraries
Use these libraries to find Vehicle Re-Identification models and implementationsDatasets
VehicleID
VeRi-776
CityFlow
VeRi-Wild
VehicleX
VRAI
Vehicle-Rear
Vehicle-1M
Car datasets in multiple scenes
Latest papers with no code
A Novel Dual-pooling Attention Module for UAV Vehicle Re-identification
Therefore, this paper proposes a novel dual-pooling attention (DpA) module, which achieves the extraction and enhancement of locally important information about vehicles from both channel and spatial dimensions by constructing two branches of channel-pooling attention (CpA) and spatial-pooling attention (SpA), and employing multiple pooling operations to enhance the attention to fine-grained information of vehicles.
Multi-query Vehicle Re-identification: Viewpoint-conditioned Network, Unified Dataset and New Metric
Existing vehicle re-identification methods mainly rely on the single query, which has limited information for vehicle representation and thus significantly hinders the performance of vehicle Re-ID in complicated surveillance networks.
ConMAE: Contour Guided MAE for Unsupervised Vehicle Re-Identification
With the large-scale and dynamic road environment, the paradigm of supervised vehicle re-identification shows limited scalability because of the heavy reliance on large-scale annotated datasets.
Complete Solution for Vehicle Re-ID in Surround-view Camera System
Vehicle re-identification (Re-ID) is a critical component of the autonomous driving perception system, and research in this area has accelerated in recent years.
Enhanced Vehicle Re-identification for ITS: A Feature Fusion approach using Deep Learning
In this paper, a framework is developed to perform the re-identification of vehicles across CCTV cameras.
Scalable Vehicle Re-Identification via Self-Supervision
As Computer Vision technologies become more mature for intelligent transportation applications, it is time to ask how efficient and scalable they are for large-scale and real-time deployment.
Discriminative-Region Attention and Orthogonal-View Generation Model for Vehicle Re-Identification
Finally, the distance between vehicle appearances is presented by the discriminative region features and multi-view features together.
Global-Supervised Contrastive Loss and View-Aware-Based Post-Processing for Vehicle Re-Identification
The proposed VABPP method is the first time that the view-aware-based method is used as a post-processing method in the field of vehicle re-identification.
Self-aligned Spatial Feature Extraction Network for UAV Vehicle Re-identification
Extensive experiments are conducted on UAV-VeID dataset, and our method achieves the best performance compared with recent ReID works.
DVHN: A Deep Hashing Framework for Large-scale Vehicle Re-identification
Specifically, we directly constrain the output from the convolutional neural network to be discrete binary codes and ensure the learned binary codes are optimal for classification.
