Just for a collection. I do not work on this topic.
49,357 images of 776 vehicles from 20 cameras. Like Market-1501 protocol.
90,196 images of 10,319 vehicles. Only two camera views??
with attribute.
47,123 images from two cameras & lablled on pair.
no ID lablled.
136,726 + 27,618 images of 1,716 cars with attributes. After crop, 136,713.
16,185 images of 196 classes.
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VR-PROUD: Vehicle Re-identification using PROgressive Unsupervised Deep architecture (PR) paper
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Embedding Adversarial Learning for Vehicle Re-Identification (IP) paper
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Viewpoint-aware Attentive Multi-view Inference for Vehicle Re-identification (CVPR) pdf
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Unsupervised Vehicle Re-Identification using Triplet Networks (CVPR workshop) pdf
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Vehicle Re-Identification with the Space-Time Prior (CVPR workshop) pdf
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Fast vehicle identification via ranked semantic sampling based embedding (IJCAI) pdf
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Vehicle re-identification by deep hidden multi-view inference (IP) paper
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Ram: a region-aware deep model for vehicle re-identification (ICME) pdf
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Learning Coarse-to-Fine Structured Feature Embedding for Vehicle Re-Identification (AAAI) pdf
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PROVID- Progressive and Multimodal Vehicle Reidentification for Large-Scale Urban Surveillance (MM) paper
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Group Sensitive Triplet Embedding for Vehicle Re-identification (MM) paper
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VP-ReID: vehicle and person re-identification system (ACMMM) paper
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Orientation Invariant Feature Embedding and Spatial Temporal Regularization for Vehicle Re-Identification (ICCV) pdf
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Learning Deep Neural Networks for Vehicle Re-ID With Visual-Spatio-Temporal Path Proposals (ICCV) pdf
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Exploiting Multi-Grain Ranking Constraints for Precisely Searching Visually-similar Vehicles (ICCV) pdf
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Improving triplet-wise training of convolutional neural network for vehicle re-identification (ICME) paper
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Deep hashing with multi-task learning for large-scale instance-level vehicle search (ICME workshop) paper
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Multi-modal metric learning for vehicle re-identification in traffic surveillance environment paper
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Vehicle re-identification by fusing multiple deep neural networks paper
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Vehicle Re-Identification for Automatic Video Traffic Surveillance (CVPR workshop) pdf
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Deep Relative Distance Learning- Tell the Difference Between Similar Vehicles (CVPR) pdf
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A Deep Learning-Based Approach to Progressive Vehicle Re-identification for Urban Surveillance (ECCV) paper
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Large-Scale Vehicle Re-Identification in Urban Surveillance Videos (ICME) paper
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- Orientation Invariant Feature Embedding and Spatial Temporal Regularization for Vehicle Re-identification (ICCV2017)
Comments: Use multiple training sets.
- Learning Deep Neural Networks for Vehicle Re-ID with Visual-spatio-temporal Path Proposals (ICCV2017)
Comments: Add the time constraint.
- Exploiting Multi-Grain Ranking Constraints for Precisely Searching Visually-similar Vehicles (ICCV2017)
Comments: Propose a dataset.
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Viewpoint-aware Attentive Multi-view Inference for Vehicle Re-identification (CVPR2018)
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Group sensitive triplet embedding for vehicle re-identification (TMM)
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Deep relative distance learning: Tell the difference between similar vehicles. (CVPR2016)
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Coarse-to-fine: A RNN-based hierarchical attention model for vehicle re-identification. (ACCV2018) ~~