Papers Domain Adaptive Person Re-Identification
“Domain Adaptive Person Re-Identification” 태그가 달린 논문 29편 · 필터 해제
Anti-Forgetting Adaptation for Unsupervised Person Re-identification
Regular unsupervised domain adaptive person re-identification (ReID) focuses on adapting a model from a source domain to a fixed target domain. However, an adapted ReID model can hardly retain previously-acquired knowled…
Domain Adaptive Person Re-IdentificationPerson Re-IdentificationUnsupervised Person Re-IdentificationCamera-Driven Representation Learning for Unsupervised Domain Adaptive Person Re-identification
We present a novel unsupervised domain adaption method for person re-identification (reID) that generalizes a model trained on a labeled source domain to an unlabeled target domain. We introduce a camera-driven curriculu…
Domain AdaptationDomain Adaptive Person Re-IdentificationPerson Re-IdentificationPseudo Label+2Color Prompting for Data-Free Continual Unsupervised Domain Adaptive Person Re-Identification
Unsupervised domain adaptive person re-identification (Re-ID) methods alleviate the burden of data annotation through generating pseudo supervision messages. However, real-world Re-ID systems, with continuously accumulat…
Domain Adaptive Person Re-IdentificationPerson Re-IdentificationStyle TransferDomain-adaptive Person Re-identification without Cross-camera Paired Samples
Existing person re-identification (re-ID) research mainly focuses on pedestrian identity matching across cameras in adjacent areas. However, in reality, it is inevitable to face the problem of pedestrian identity matchin…
Domain Adaptive Person Re-IdentificationPerson Re-IdentificationUnsupervised Domain Adaptation for Cross-Regional Scenes Person Re-identification
In large-scale surveillance systems, the absence of positive cross-camera pedestrian samples in cross-regional scenes poses a limitation on the performance of person re-identification models. To tackle this challenge, an…
Domain AdaptationDomain Adaptive Person Re-IdentificationPerson Re-IdentificationStyle Transfer+1Illumination Variation Correction Using Image Synthesis For Unsupervised Domain Adaptive Person Re-Identification
Unsupervised domain adaptive (UDA) person re-identification (re-ID) aims to learn identity information from labeled images in source domains and apply it to unlabeled images in a target domain. One major issue with many …
Domain Adaptive Person Re-IdentificationImage GenerationPerson Re-IdentificationUnsupervised domain-adaptive person re-identification with multi-camera constraints
Person re-identification is a key technology for analyzing video-based human behavior; however, its application is still challenging in practical situations due to the performance degradation for domains different from t…
Domain Adaptive Person Re-IdentificationPerson Re-IdentificationFeature Diversity Learning with Sample Dropout for Unsupervised Domain Adaptive Person Re-identification
Clustering-based approach has proved effective in dealing with unsupervised domain adaptive person re-identification (ReID) tasks. However, existing works along this approach still suffer from noisy pseudo labels and the…
DiversityDomain Adaptive Person Re-IdentificationPerson Re-IdentificationUnsupervised Domain Adaptive Person Re-id with Local-enhance and Prototype Dictionary Learning
The unsupervised domain adaptive person re-identification (re-ID) task has been a challenge because, unlike the general domain adaptive tasks, there is no overlap between the classes of source and target domain data in t…
Contrastive LearningDictionary LearningDomain AdaptationDomain Adaptive Person Re-Identification+1Delving into Probabilistic Uncertainty for Unsupervised Domain Adaptive Person Re-Identification
Clustering-based unsupervised domain adaptive (UDA) person re-identification (ReID) reduces exhaustive annotations. However, owing to unsatisfactory feature embedding and imperfect clustering, pseudo labels for target do…
ClusteringDomain Adaptive Person Re-IdentificationPerson Re-IdentificationMulti-Centroid Representation Network for Domain Adaptive Person Re-ID
Recently, many approaches tackle the Unsupervised Domain Adaptive person re-identification (UDA re-ID) problem through pseudo-label-based contrastive learning. During training, a uni-centroid representation is obtained b…
Contrastive LearningDomain Adaptive Person Re-IdentificationPerson Re-IdentificationPseudo LabelLifelong Unsupervised Domain Adaptive Person Re-identification with Coordinated Anti-forgetting and Adaptation
Unsupervised domain adaptive person re-identification (ReID) has been extensively investigated to mitigate the adverse effects of domain gaps. Those works assume the target domain data can be accessible all at once. Howe…
Domain Adaptive Person Re-IdentificationKnowledge DistillationMemorizationPerson Re-Identification+2Unsupervised Domain Adaptive Person Re-Identification via Human Learning Imitation
Unsupervised domain adaptive person re-identification has received significant attention due to its high practical value. In past years, by following the clustering and finetuning paradigm, researchers propose to utilize…
Domain Adaptive Person Re-IdentificationPerson Re-IdentificationIDM: An Intermediate Domain Module for Domain Adaptive Person Re-ID
Unsupervised domain adaptive person re-identification (UDA re-ID) aims at transferring the labeled source domain's knowledge to improve the model's discriminability on the unlabeled target domain. From a novel perspectiv…
DiversityDomain Adaptive Person Re-IdentificationPerson Re-IdentificationGraph Consistency Based Mean-Teaching for Unsupervised Domain Adaptive Person Re-Identification
Recent works show that mean-teaching is an effective framework for unsupervised domain adaptive person re-identification. However, existing methods perform contrastive learning on selected samples between teacher and stu…
Contrastive LearningDomain Adaptive Person Re-IdentificationPerson Re-IdentificationRepresentation LearningDisentanglement-based Cross-Domain Feature Augmentation for Effective Unsupervised Domain Adaptive Person Re-identification
Unsupervised domain adaptive (UDA) person re-identification (ReID) aims to transfer the knowledge from the labeled source domain to the unlabeled target domain for person matching. One challenge is how to generate target…
DisentanglementDiversityDomain Adaptive Person Re-Identificationdomain classification+1Group-aware Label Transfer for Domain Adaptive Person Re-identification
Unsupervised Domain Adaptive (UDA) person re-identification (ReID) aims at adapting the model trained on a labeled source-domain dataset to a target-domain dataset without any further annotations. Most successful UDA-ReI…
AttributeClusteringDomain Adaptive Person Re-IdentificationOnline Clustering+3Dual-Refinement: Joint Label and Feature Refinement for Unsupervised Domain Adaptive Person Re-Identification
Unsupervised domain adaptive (UDA) person re-identification (re-ID) is a challenging task due to the missing of labels for the target domain data. To handle this problem, some recent works adopt clustering algorithms to …
ClusteringDomain Adaptive Person Re-IdentificationPerson Re-IdentificationExploiting Sample Uncertainty for Domain Adaptive Person Re-Identification
Many unsupervised domain adaptive (UDA) person re-identification (ReID) approaches combine clustering-based pseudo-label prediction with feature fine-tuning. However, because of domain gap, the pseudo-labels are not alwa…
ClusteringDomain Adaptive Person Re-IdentificationPerson Re-IdentificationPseudo Label+2Domain Adaptive Person Re-Identification via Coupling Optimization
Domain adaptive person Re-Identification (ReID) is challenging owing to the domain gap and shortage of annotations on target scenarios. To handle those two challenges, this paper proposes a coupling optimization method i…
Domain Adaptive Person Re-IdentificationPerson Re-IdentificationTransfer LearningUnsupervised Person Re-Identification