SOTAVerified

Vehicle Re-Identification

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 )

Papers

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Showing 101–150 of 150 papers

TitleStatusHype
VERI-Wild: A Large Dataset and a New Method for Vehicle Re-Identification in the Wild—0
A Comprehensive Survey on Deep-Learning-based Vehicle Re-Identification: Models, Data Sets and Challenges—0
SemHARQ: Semantic-Aware HARQ for Multi-task Semantic Communications—0
Coarse-to-fine: A RNN-based hierarchical attention model for vehicle re-identification—0
Cluster images with AntClust: a clustering algorithm based on the chemical recognition system of ants—0
CLIP-SENet: CLIP-based Semantic Enhancement Network for Vehicle Re-identification—0
Spatial-temporal Vehicle Re-identification—0
StRDAN: Synthetic-to-Real Domain Adaptation Network for Vehicle Re-Identification—0
CityFlow: A City-Scale Benchmark for Multi-Target Multi-Camera Vehicle Tracking and Re-Identification—0
Stripe-based and Attribute-aware Network: A Two-Branch Deep Model for Vehicle Re-identification—0
Study on Aspect Ratio Variability toward Robustness of Vision Transformer-based Vehicle Re-identification—0
Background Segmentation for Vehicle Re-Identification—0
The 4th AI City Challenge—0
A unified neural network for object detection, multiple object tracking and vehicle re-identification—0
The Devil is in the Details: Self-Supervised Attention for Vehicle Re-Identification—0
Traffic-Aware Multi-Camera Tracking of Vehicles Based on ReID and Camera Link Model—0
Attributes Guided Feature Learning for Vehicle Re-identification—0
Trends in Vehicle Re-identification Past, Present, and Future: A Comprehensive Review—0
Viewpoint-Aware Attentive Multi-View Inference for Vehicle Re-Identification—0
Viewpoint-Aware Channel-Wise Attentive Network for Vehicle Re-Identification—0
UAV (Unmanned Aerial Vehicles): Diverse Applications of UAV Datasets in Segmentation, Classification, Detection, and Tracking—0
UCM-VeID V2: A Richer Dataset and A Pre-training Method for UAV Cross-Modality Vehicle Re-Identification—0
AttributeNet: Attribute Enhanced Vehicle Re-Identification—0
Attribute-guided Feature Learning Network for Vehicle Re-identification—0
Unity in Diversity: Multi-expert Knowledge Confrontation and Collaboration for Generalizable Vehicle Re-identification—0
Unsupervised Vehicle Re-Identification Based on Cross-Style Semi-Supervised Pre-Training and Feature Cross-Division—0
Attribute-guided Feature Extraction and Augmentation Robust Learning for Vehicle Re-identification—0
Unsupervised Vehicle Re-identification with Progressive Adaptation—0
A survey of advances in vision-based vehicle re-identification—0
Vehicle Detection and Tracking From Surveillance Cameras in Urban Scenes—0
VehicleGAN: Pair-flexible Pose Guided Image Synthesis for Vehicle Re-identification—0
A Novel Dual-pooling Attention Module for UAV Vehicle Re-identification—0
Viewpoint-aware Progressive Clustering for Unsupervised Vehicle Re-identification—0
Vehicle Re-Identification: an Efficient Baseline Using Triplet Embedding—0
A Deep Learning-Based Approach to Progressive Vehicle Re-identification for Urban Surveillance—0
Vehicle Re-identification Based on Dual Distance Center Loss—0
Vision-based Vehicle Re-identification in Bridge Scenario using Flock Similarity—0
Vehicle Re-identification in Aerial Imagery: Dataset and Approach—0
Enhanced Vehicle Re-identification for ITS: A Feature Fusion approach using Deep Learning—0
Vehicle Re-Identification in Context—0
Vehicle Re-identification Method Based on Vehicle Attribute and Mutual Exclusion Between Cameras—0
Eliminating cross-camera bias for vehicle re-identification—0
DVHN: A Deep Hashing Framework for Large-scale Vehicle Re-identification—0
GiT: Graph Interactive Transformer for Vehicle Re-identification—0
Global-Supervised Contrastive Loss and View-Aware-Based Post-Processing for Vehicle Re-Identification—0
Dual-Level Viewpoint-Learning for Cross-Domain Vehicle Re-Identification—0
Image-based Vehicle Re-identification Model with Adaptive Attention Modules and Metadata Re-ranking—0
Image-to-image domain adaptation for vehicle re-identification—0
Dual Embedding Expansion for Vehicle Re-identification—0
LABNet: Local Graph Aggregation Network with Class Balanced Loss for Vehicle Re-Identification—0
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All datasetsVeRi-776VehicleID SmallVehicleID LargeVehicleID MediumVRAI test-devVeRi-Wild SmallVRAI testVeRiVeRi-Wild LargeCityFlowVehicleIDVeRi-Wild Medium

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MBR4B-LAI (w/ RK)mAP92.1—Unverified
2RPTMmAP88—Unverified
3A Strong BaselinemAP87.1—Unverified
4MBR4B-LAI (without re-ranking)mAP86—Unverified
5MBR4B (without re-ranking)mAP84.72—Unverified
6CLIP-ReID (without re-ranking)mAP84.5—Unverified
7VehicleNetmAP83.41—Unverified
8ProNet++ (ResNet50)mAP83.4—Unverified
9TransReIDmAP82.3—Unverified
10CA-JaccardmAP81.4—Unverified
#ModelMetricClaimedVerifiedStatus
1Recall@k Surrogate loss (ViT-B/16)Rank-196.2—Unverified
2Recall@k Surrogate loss (ResNet-50)Rank-195.7—Unverified
3RPTMRank-195.5—Unverified
4PNP LossRank-195.5—Unverified
5Smooth-APRank-194.9—Unverified
6MBR-4B (without RK)Rank-188.3—Unverified
7ANetRank-187.9—Unverified
8CLIP-ReID (without re-ranking)Rank-185.5—Unverified
9GiTRank184.65—Unverified
10HPGNRank183.91—Unverified
#ModelMetricClaimedVerifiedStatus
1Recall@k Surrogate loss (ViT-B/16)Rank-194.7—Unverified
2Recall@k Surrogate loss (ResNet-50)Rank-193.8—Unverified
3PNP LossRank-193.2—Unverified
4RPTMRank-192.9—Unverified
5Smooth-APRank-191.9—Unverified
6ANetRank-180.5—Unverified
7vehiclenetRank-179.46—Unverified
8MSINet (2.3M w/o RK)Rank-177.9—Unverified
9CALRank-175.1—Unverified
10QD-DLFmAP68.41—Unverified
#ModelMetricClaimedVerifiedStatus
1Recall@k Surrogate loss (ViT-B/16)Rank-195.2—Unverified
2Recall@k Surrogate loss (ResNet-50)Rank-194.6—Unverified
3PNP LossRank-194.2—Unverified
4Smooth-APRank-193.3—Unverified
5RPTMRank-193.3—Unverified
6ANetRank-182.8—Unverified
7vehiclenetRank-181.35—Unverified
8CALRank-178.2—Unverified
9QD-DLFmAP74.63—Unverified
#ModelMetricClaimedVerifiedStatus
1abu_0916MAP0.78—Unverified
2Baseline ModelMAP0.78—Unverified
3Juice LeeMAP0.7—Unverified
4nangggMAP0.63—Unverified
5asdfMAP0.62—Unverified
692MAP0.56—Unverified
#ModelMetricClaimedVerifiedStatus
1MBR-4B (without RK)Rank196.6—Unverified
2ANetRank196.5—Unverified
3ResNet50-IBNmAP73.4—Unverified
#ModelMetricClaimedVerifiedStatus
1Baseline ModelMAP0.79—Unverified
2Juice LeeMAP0.69—Unverified
3nangggMAP0.62—Unverified
#ModelMetricClaimedVerifiedStatus
1vehiclenetmAP83.41—Unverified
2VKD (ResVKD-50)mAP82.2—Unverified
#ModelMetricClaimedVerifiedStatus
1ANetmAP75.9—Unverified
2ResNet50-IBNmAP58.62—Unverified
#ModelMetricClaimedVerifiedStatus
1A Strong BaselinemAP61.34—Unverified
#ModelMetricClaimedVerifiedStatus
1VehicleNetRank183.64—Unverified
#ModelMetricClaimedVerifiedStatus
1ANetRank195.2—Unverified