Papers Unsupervised Vehicle Re-Identification
“Unsupervised Vehicle Re-Identification” 태그가 달린 논문 13편 · 필터 해제
Revisiting Multi-Granularity Representation via Group Contrastive Learning for Unsupervised Vehicle Re-identification
Vehicle re-identification (Vehicle ReID) aims at retrieving vehicle images across disjoint surveillance camera views. The majority of vehicle ReID research is heavily reliant upon supervisory labels from specific human-c…
Contrastive LearningDomain AdaptationUnsupervised Domain AdaptationUnsupervised Vehicle Re-Identification+1CA-Jaccard: Camera-aware Jaccard Distance for Person Re-identification
Person re-identification (re-ID) is a challenging task that aims to learn discriminative features for person retrieval. In person re-ID, Jaccard distance is a widely used distance metric, especially in re-ranking and clu…
Person Re-IdentificationPerson RetrievalRe-RankingUnsupervised Person Re-Identification+2Prototypical Contrastive Learning-based CLIP Fine-tuning for Object Re-identification
This work aims to adapt large-scale pre-trained vision-language models, such as contrastive language-image pretraining (CLIP), to enhance the performance of object reidentification (Re-ID) across various supervision sett…
Contrastive LearningPerson Re-IdentificationPrompt LearningUnsupervised Person Re-Identification+1Multi‑camera trajectory matching based on hierarchical clustering and constraints
The fast improvement of deep learning methods resulted in breakthroughs in image classification, object detection, and object tracking. Autonomous driving and traffic monitoring systems, especially the on-premise install…
AttributeAutonomous DrivingConstrained Clusteringimage-classification+8Unsupervised Vehicle Re-Identification Based on Cross-Style Semi-Supervised Pre-Training and Feature Cross-Division
Vehicle Re-Identification (Re-ID) based on Unsupervised Domain Adaptation (UDA) has shown promising performance. However, two main issues still exist: (1) existing methods that use Generative Adversarial Networks (GANs) …
Domain AdaptationPseudo LabelStyle TransferUnsupervised Domain Adaptation+2ConMAE: Contour Guided MAE for Unsupervised Vehicle Re-Identification
Vehicle re-identification is a cross-view search task by matching the same target vehicle from different perspectives. It serves an important role in road-vehicle collaboration and intelligent road control. With the larg…
Self-Supervised LearningUnsupervised Vehicle Re-IdentificationVehicle Re-IdentificationTriplet Contrastive Representation Learning for Unsupervised Vehicle Re-identification
Part feature learning is critical for fine-grained semantic understanding in vehicle re-identification. However, existing approaches directly model part features and global features, which can easily lead to serious grad…
Contrastive LearningRepresentation LearningTripletUnsupervised Vehicle Re-Identification+1Part-based Pseudo Label Refinement for Unsupervised Person Re-identification
Unsupervised person re-identification (re-ID) aims at learning discriminative representations for person retrieval from unlabeled data. Recent techniques accomplish this task by using pseudo-labels, but these labels are …
Person Re-IdentificationPerson RetrievalPseudo LabelRetrieval+2Camera-Tracklet-Aware Contrastive Learning for Unsupervised Vehicle Re-Identification
Recently, vehicle re-identification methods based on deep learning constitute remarkable achievement. However, this achievement requires large-scale and well-annotated datasets. In constructing the dataset, assigning glo…
Contrastive LearningDomain AdaptationUnsupervised Vehicle Re-IdentificationVehicle Re-IdentificationUnsupervised Vehicle Re-Identification via Self-supervised Metric Learning using Feature Dictionary
The key challenge of unsupervised vehicle re-identification (Re-ID) is learning discriminative features from unlabelled vehicle images. Numerous methods using domain adaptation have achieved outstanding performance, but …
Domain AdaptationMetric LearningTripletUnsupervised Vehicle Re-Identification+1Viewpoint-aware Progressive Clustering for Unsupervised Vehicle Re-identification
Vehicle re-identification (Re-ID) is an active task due to its importance in large-scale intelligent monitoring in smart cities. Despite the rapid progress in recent years, most existing methods handle vehicle Re-ID task…
ClusteringDomain AdaptationUnsupervised Vehicle Re-IdentificationVehicle Re-IdentificationUnsupervised Vehicle Re-identification with Progressive Adaptation
Vehicle re-identification (reID) aims at identifying vehicles across different non-overlapping cameras views. The existing methods heavily relied on well-labeled datasets for ideal performance, which inevitably causes fa…
Unsupervised Domain AdaptationUnsupervised Vehicle Re-IdentificationVehicle Re-IdentificationCross Domain Knowledge Transfer for Unsupervised Vehicle Re-identification
Vehicle re-identification (reID) is to identify a target vehicle in different cameras with non-overlapping views. When deploy the well-trained model to a new dataset directly, there is a severe performance drop because o…
Domain AdaptationGenerative Adversarial NetworkImage-to-Image TranslationTransfer Learning+3