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Self-paced contrastive learning with hybrid memory for domain adaptive object re-id
Abstract Domain adaptive object re-ID aims to transfer the learned knowledge from the
labeled source domain to the unlabeled target domain to tackle the open-class re …
labeled source domain to the unlabeled target domain to tackle the open-class re …
Refining pseudo labels with clustering consensus over generations for unsupervised object re-identification
Unsupervised object re-identification targets at learning discriminative representations for
object retrieval without any annotations. Clustering-based methods conduct training with the …
object retrieval without any annotations. Clustering-based methods conduct training with the …
Online pseudo label generation by hierarchical cluster dynamics for adaptive person re-identification
Adaptive person re-identification (adaptive ReID) targets at transferring learned knowledge
from the labeled source domain to the unlabeled target domain. Pseudo-label-based …
from the labeled source domain to the unlabeled target domain. Pseudo-label-based …
Exploiting sample uncertainty for domain adaptive person re-identification
Many unsupervised domain adaptive (UDA) person ReID approaches combine clustering-
based pseudo-label prediction with feature fine-tuning. However, because of domain gap …
based pseudo-label prediction with feature fine-tuning. However, because of domain gap …
Learning to purification for unsupervised person re-identification
Unsupervised person re-identification is a challenging and promising task in computer
vision. Nowadays unsupervised person re-identification methods have achieved great …
vision. Nowadays unsupervised person re-identification methods have achieved great …
Hybrid dynamic contrast and probability distillation for unsupervised person re-id
Unsupervised person re-identification (Re-Id) has attracted increasing attention due to its
practical application in the read-world video surveillance system. The traditional …
practical application in the read-world video surveillance system. The traditional …
Translation, association and augmentation: Learning cross-modality re-identification from single-modality annotation
Daytime visible modality (RGB) and night-time infrared (IR) modality person re-identification
(VI-ReID) is a challenging cross-modality pedestrian retrieval problem. However, training a …
(VI-ReID) is a challenging cross-modality pedestrian retrieval problem. However, training a …
Delving 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 …
reduces exhaustive annotations. However, owing to unsatisfactory feature embedding and …
Unsupervised domain adaptation through dynamically aligning both the feature and label spaces
In unsupervised domain adaptation (UDA), a target-domain model is trained by the
supervised knowledge from a source domain. Although UDA has recently received much …
supervised knowledge from a source domain. Although UDA has recently received much …
Meta pairwise relationship distillation for unsupervised person re-identification
Unsupervised person re-identification (Re-ID) remains challenging due to the lack of ground-
truth labels. Existing methods often rely on estimated pseudo labels via iterative clustering …
truth labels. Existing methods often rely on estimated pseudo labels via iterative clustering …