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
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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
Vehicle Detection and Tracking From Surveillance Cameras in Urban Scenes
Detecting and tracking vehicles in urban scenes is a crucial step in many traffic-related applications as it helps to improve road user safety among other benefits.
Learning Canonical 3D Object Representation for Fine-Grained Recognition
By incorporating 3D shape and appearance jointly in a deep representation, our method learns the discriminative representation of the object and achieves competitive performance on fine-grained image recognition and vehicle re-identification.
Weakly-supervised Part-Attention and Mentored Networks for Vehicle Re-Identification
Current part-level feature learning methods typically detect vehicle parts via uniform division, outside tools, or attention modeling.
GiT: Graph Interactive Transformer for Vehicle Re-identification
In the macro view, a list of GiT blocks are stacked to build a vehicle re-identification model, in where graphs are to extract discriminative local features within patches and transformers are to extract robust global features among patches.
Moving Towards Centers: Re-ranking with Attention and Memory for Re-identification
Specifically, all the feature embeddings of query and gallery images are expanded and enhanced by a linear combination of their neighbors, with the correlation prediction serving as discriminative combination weights.
Vehicle Re-identification Method Based on Vehicle Attribute and Mutual Exclusion Between Cameras
Vehicle Re-identification aims to identify a specific vehicle across time and camera view.
Multi-Attention-Based Soft Partition Network for Vehicle Re-Identification
Meanwhile, based on the researchers' insights, various handcrafted multi-attention architectures for specific viewpoints or vehicle parts have been proposed.
Pluggable Weakly-Supervised Cross-View Learning for Accurate Vehicle Re-Identification
Learning cross-view consistent feature representation is the key for accurate vehicle Re-identification (ReID), since the visual appearance of vehicles changes significantly under different viewpoints.
Trends in Vehicle Re-identification Past, Present, and Future: A Comprehensive Review
Vehicle Re-identification (re-id) over surveillance camera network with non-overlapping field of view is an exciting and challenging task in intelligent transportation systems (ITS).
AttributeNet: Attribute Enhanced Vehicle Re-Identification
Vehicle Re-Identification (V-ReID) is a critical task that associates the same vehicle across images from different camera viewpoints.
