stephencurry303 / vehicle-re-identification-paper

review of papers of vehicle re-identification

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vehicle-re-identification-paper

review of papers of vehicle re-identification

dataset

paper of dataset

VeRi

  1. Large-Scale Vehicle Re-Identification in Urban Surveillance Videos [ICME2016]

  2. Improving triplet-wise training of convolutional neural network for vehicle re-identification [ICME2017]

  3. A Shortly and Densely Connected Convolutional Neural Network for Vehicle Re-identification [ICPR2018]

  4. Joint Feature and Similarity Deep Learning for Vehicle Re-identification [IEEE2018]

  5. Vehicle re-identification using quadruple directional deep learning features [IEEE2019]

VeRi-776

  1. A Deep Learning-Based Approach to Progressive Vehicle Re-identification for Urban Surveillance [ECCV2016]

  2. Learning Deep Neural Networks for Vehicle Re-ID With Visual-Spatio-Temporal Path Proposals [ICCV2017]

  3. Orientation Invariant Feature Embedding and Spatial Temporal Regularization for Vehicle Re-Identification [ICCV2017]

  4. Multi-modal metric learning for vehicle re-identification in traffic surveillance environment [ICIP2017]

  5. Viewpoint-aware Attentive Multi-view Inference for Vehicle Re-identification [CVPR2018]

  6. Vehicle Re-Identification in Context [18]

  7. Multi-attribute driven vehicle re-identification with spatial-temporal re-ranking [ICIP2018]

  8. Joint Semi-supervised Learning and Re-ranking for Vehicle Re-identification [ICPR2018]

  9. PROVID- Progressive and Multimodal Vehicle Reidentification for Large-Scale Urban Surveillance [MM2018]

  10. Vehicle re-identification by deep hidden multi-view inference [IP2018]

  11. Group Sensitive Triplet Embedding for Vehicle Re-identification [MM2018]

  12. Ram: a region-aware deep model for vehicle re-identification [ICME2018]

  13. Vehicle Re-identification by Adversarial Bi-directional LSTM Network [WACV2018]

  14. Part-regularized Near-duplicate Vehicle Re-identification [IEEE2019]

  15. VERI-Wild: A Large Dataset and a New Method for Vehicle Re-Identification in the Wild [CVPR2019]

  16. Partition and Reunion: A Two-Branch Neural Network for Vehicle Re-identification [IEEE2019]

  17. A Dual-Path Model With Adaptive Attention For Vehicle Re-Identification [ICCV2019]

  18. Vehicle Re-identification with Viewpoint-aware Metric Learning [ICCV2019]

  19. Vehicle Re-Identification by Multi-Grain Learning [ICIP2019]

  20. Embedding Adversarial Learning for Vehicle Re-Identification [IP2019]

  21. Multi-label learning with multi-label smoothing regularization for vehicle re-identification [NC2019]

  22. VR-PROUD: Vehicle Re-identification using PROgressive Unsupervised Deep architecture [PR2019]

  23. PVSS: A Progressive Vehicle Search System for Video Surveillance Networks [2019]

  24. Vehicle Re-Identification: an Efficient Baseline Using Triplet Embedding [2019]

VehicleID

  1. Deep Relative Distance Learning- Tell the Difference Between Similar Vehicles [CVPR2016]

  2. Vehicle Re-Identification by Fine-Grained Cross-Level Deep Learning [BMVC2017]

  3. Orientation Invariant Feature Embedding and Spatial Temporal Regularization for Vehicle Re-Identification [ICCV2017]

  4. Deep joint discriminative learning for vehicle re-identification and retrieval [ICIP2017]

  5. Improving triplet-wise training of convolutional neural network for vehicle re-identification [ICME2017]

  6. Vehicle re-identification by fusing multiple deep neural networks [IPTA2017]

  7. Learning Coarse-to-Fine Structured Feature Embedding for Vehicle Re-Identification [AAAI]

  8. Viewpoint-aware Attentive Multi-view Inference for Vehicle Re-identification [CVPR2018]

  9. Vehicle Re-Identification in Context [18]

  10. Multi-attribute driven vehicle re-identification with spatial-temporal re-ranking [ICIP2018]

  11. A Shortly and Densely Connected Convolutional Neural Network for Vehicle Re-identification [ICPR2018]

  12. Joint Semi-supervised Learning and Re-ranking for Vehicle Re-identification [ICPR2018]

  13. Part-based Multi-stream Model for Vehicle Searching [ICPR2018]

  14. Joint Feature and Similarity Deep Learning for Vehicle Re-identification [IEEE2018]

  15. PROVID- Progressive and Multimodal Vehicle Reidentification for Large-Scale Urban Surveillance [MM2018]

  16. Vehicle re-identification by deep hidden multi-view inference [IP2018]

  17. Group Sensitive Triplet Embedding for Vehicle Re-identification [MM2018]

  18. Ram: a region-aware deep model for vehicle re-identification [ICME2018]

  19. Vehicle Re-identification by Adversarial Bi-directional LSTM Network [WACV2018]

  20. Part-regularized Near-duplicate Vehicle Re-identification [IEEE2019]

  21. VERI-Wild: A Large Dataset and a New Method for Vehicle Re-Identification in the Wild [CVPR2019]

  22. Partition and Reunion: A Two-Branch Neural Network for Vehicle Re-identification [IEEE2019]

  23. A Dual-Path Model With Adaptive Attention For Vehicle Re-Identification [ICCV2019]

  24. Vehicle Re-identification with Viewpoint-aware Metric Learning [ICCV2019]

  25. Vehicle Re-Identification by Multi-Grain Learning [ICIP2019]

  26. Embedding Adversarial Learning for Vehicle Re-Identification [IP2019]

  27. Two-Level Attention Network with Multi-Grain Ranking Loss for Vehicle Re-Identification [IEEE2019]

  28. Vehicle re-identification using quadruple directional deep learning features [IEEE2019]

  29. Multi-label learning with multi-label smoothing regularization for vehicle re-identification [NC2019]

  30. VR-PROUD: Vehicle Re-identification using PROgressive Unsupervised Deep architecture [PR2019]

  31. Structural Analysis of Attributes for Vehicle Re-Identification and Retrieval [IEEE2019]

  32. Vehicle Re-Identification with Refined Part Model [ICMEW2019]

  33. Vehicle Re-Identification: an Efficient Baseline Using Triplet Embedding [2019]

CompCars

  1. Deep Relative Distance Learning- Tell the Difference Between Similar Vehicles [CVPR2016]

  2. Orientation Invariant Feature Embedding and Spatial Temporal Regularization for Vehicle Re-Identification [ICCV2017]

  3. Group Sensitive Triplet Embedding for Vehicle Re-identification [MM2018]

PKU-VD

  1. Exploiting Multi-Grain Ranking Constraints for Precisely Searching Visually-similar Vehicles [ICCV2017]

  2. Vehicle Re-Identification: an Efficient Baseline Using Triplet Embedding [2019]

BoxCars21K

  1. Orientation Invariant Feature Embedding and Spatial Temporal Regularization for Vehicle Re-Identification [ICCV2017]

VRID-1

  1. VRID-1: A Basic Vehicle Re-identification Dataset for Similar Vehicles [IEEE2017]

Vehicle-1M

  1. Learning Coarse-to-Fine Structured Feature Embedding for Vehicle Re-Identification [AAAI]

  2. Two-Level Attention Network with Multi-Grain Ranking Loss for Vehicle Re-Identification [IEEE2019]

  3. Vehicle Re-Identification with Refined Part Model [ICMEW2019]

VRIC

  1. Vehicle Re-Identification in Context [18]

  2. Partition and Reunion: A Two-Branch Neural Network for Vehicle Re-identification [IEEE2019]

Toy Car RE-ID

  1. Vehicle re-identification by deep hidden multi-view inference [IP2018]

Multi-View Car Dataset

  1. Vehicle re-identification by deep hidden multi-view inference [IP2018]

PKU-Vehicle

  1. Group Sensitive Triplet Embedding for Vehicle Re-identification [MM2018]

VERI-Wild

  1. VERI-Wild: A Large Dataset and a New Method for Vehicle Re-Identification in the Wild [CVPR2019]

CityFlow-ReID

  1. Partition and Reunion: A Two-Branch Neural Network for Vehicle Re-identification [IEEE2019]

VAC21

  1. Structural Analysis of Attributes for Vehicle Re-Identification and Retrieval [IEEE2019]

paper

2016

  1. Vehicle Re-Identification for Automatic Video Traffic Surveillance [CVPR2016]

  2. Deep Relative Distance Learning- Tell the Difference Between Similar Vehicles [CVPR2016]

  3. A Deep Learning-Based Approach to Progressive Vehicle Re-identification for Urban Surveillance [ECCV2016]

  4. Large-Scale Vehicle Re-Identification in Urban Surveillance Videos [ICME2016]

2017

  1. Orientation Invariant Feature Embedding and Spatial Temporal Regularization for Vehicle Re-Identification [ICCV2017]

  2. Learning Deep Neural Networks for Vehicle Re-ID With Visual-Spatio-Temporal Path Proposals [ICCV2017]

  3. Exploiting Multi-Grain Ranking Constraints for Precisely Searching Visually-similar Vehicles [ICCV2017]

  4. Improving triplet-wise training of convolutional neural network for vehicle re-identification [ICME2017]

  5. Deep hashing with multi-task learning for large-scale instance-level vehicle search [ICME2017]

  6. Deep joint discriminative learning for vehicle re-identification and retrieval [ICIP2017]

  7. Vehicle Re-Identification by Fine-Grained Cross-Level Deep Learning [BMVC2017]

  8. Multi-modal metric learning for vehicle re-identification in traffic surveillance environment [ICIP2017]

  9. Vehicle re-identification by fusing multiple deep neural networks [IPTA2017]

  10. VRID-1: A Basic Vehicle Re-identification Dataset for Similar Vehicles [IEEE2017]

2018

  1. Unsupervised Vehicle Re-Identification using Triplet Networks [CVPR2018]

  2. Vehicle Re-Identification with the Space-Time Prior [CVPR2018]

  3. Viewpoint-aware Attentive Multi-view Inference for Vehicle Re-identification [CVPR2018]

  4. Single-camera and inter-camera vehicle tracking and 3D speed estimation based on fusion of visual and semantic features [CVPR2018]

  5. Fast vehicle identification via ranked semantic sampling based embedding [IJCAI2018]

  6. Vehicle re-identification by deep hidden multi-view inference [IP2018]

  7. Ram: a region-aware deep model for vehicle re-identification [ICME2018]

  8. Learning Coarse-to-Fine Structured Feature Embedding for Vehicle Re-Identification [AAAI]

  9. PROVID- Progressive and Multimodal Vehicle Reidentification for Large-Scale Urban Surveillance [MM2018]

  10. Group Sensitive Triplet Embedding for Vehicle Re-identification [MM2018]

  11. VP-ReID: vehicle and person re-identification system [ACMMM2018]

  12. Multi-attribute driven vehicle re-identification with spatial-temporal re-ranking [ICIP2018]

  13. A Shortly and Densely Connected Convolutional Neural Network for Vehicle Re-identification [ICPR2018]

  14. Joint Semi-supervised Learning and Re-ranking for Vehicle Re-identification [ICPR2018]

  15. Part-based Multi-stream Model for Vehicle Searching [ICPR2018]

  16. Vehicle Re-identification by Adversarial Bi-directional LSTM Network [WACV2018]

  17. Joint Feature and Similarity Deep Learning for Vehicle Re-identification [IEEE2018]

  18. Vehicle Re-Identification in Context [18]

2019

  1. A Dual-Path Model With Adaptive Attention For Vehicle Re-Identification [ICCV2019]

  2. Vehicle Re-identification with Viewpoint-aware Metric Learning [ICCV2019]

  3. VR-PROUD: Vehicle Re-identification using PROgressive Unsupervised Deep architecture [PR2019]

  4. Embedding Adversarial Learning for Vehicle Re-Identification [IP2019]

  5. VERI-Wild: A Large Dataset and a New Method for Vehicle Re-Identification in the Wild [CVPR2019]

  6. Part-regularized Near-duplicate Vehicle Re-identification [IEEE2019]

  7. Partition and Reunion: A Two-Branch Neural Network for Vehicle Re-identification [IEEE2019]

  8. Vehicle Re-Identification by Multi-Grain Learning [ICIP2019]

  9. Two-Level Attention Network with Multi-Grain Ranking Loss for Vehicle Re-Identification [IEEE2019]

  10. Vehicle re-identification using quadruple directional deep learning features [IEEE2019]

  11. Multi-label learning with multi-label smoothing regularization for vehicle re-identification [NC2019]

  12. PVSS: A Progressive Vehicle Search System for Video Surveillance Networks [2019]

  13. Structural Analysis of Attributes for Vehicle Re-Identification and Retrieval [IEEE2019]

  14. Vehicle Re-Identification with Refined Part Model [ICMEW2019]

  15. Vehicle Re-Identification: an Efficient Baseline Using Triplet Embedding [2019]

State-of-the-art Results on the VeRi-776 and VehilceID

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review of papers of vehicle re-identification