Implicit sample extension for unsupervised person re-identification
Most existing unsupervised person re-identification (Re-ID) methods use clustering to
generate pseudo labels for model training. Unfortunately, clustering sometimes mixes …
generate pseudo labels for model training. Unfortunately, clustering sometimes mixes …
Hybrid contrastive learning for unsupervised person re-identification
Unsupervised person re-identification (Re-ID) aims to learn discriminative features without
human-annotated labels. Recently, contrastive learning has provided a new prospect for …
human-annotated labels. Recently, contrastive learning has provided a new prospect for …
Msinet: Twins contrastive search of multi-scale interaction for object reid
Abstract Neural Architecture Search (NAS) has been increasingly appealing to the society of
object Re-Identification (ReID), for that task-specific architectures significantly improve the …
object Re-Identification (ReID), for that task-specific architectures significantly improve the …
Noisy correspondence learning with meta similarity correction
Despite the success of multimodal learning in cross-modal retrieval task, the remarkable
progress relies on the correct correspondence among multimedia data. However, collecting …
progress relies on the correct correspondence among multimedia data. However, collecting …
Style uncertainty based self-paced meta learning for generalizable person re-identification
L Zhang, Z Liu, W Zhang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Domain generalizable person re-identification (DG ReID) is a challenging problem, because
the trained model is often not generalizable to unseen target domains with different …
the trained model is often not generalizable to unseen target domains with different …
Diversity feature constraint based on heterogeneous data for unsupervised person re-identification
Person re-identification (ReID) based on heterogeneous data aims to search for the same
pedestrian from different modalities. The existing unsupervised heterogeneous ReID …
pedestrian from different modalities. The existing unsupervised heterogeneous ReID …
A real-time memory updating strategy for unsupervised person re-identification
Recently, clustering-based methods have been the dominant solution for unsupervised
person re-identification (ReID). Memory-based contrastive learning is widely used for its …
person re-identification (ReID). Memory-based contrastive learning is widely used for its …
Rethinking sampling strategies for unsupervised person re-identification
Unsupervised person re-identification (re-ID) remains a challenging task. While extensive
research has focused on the framework design and loss function, this paper shows that …
research has focused on the framework design and loss function, this paper shows that …
Robust cross-domain Pseudo-labeling and contrastive learning for unsupervised domain adaptation NIR-VIS face recognition
Near-infrared and visible face recognition (NIR-VIS) is attracting increasing attention
because of the need to achieve face recognition in low-light conditions to enable 24-hour …
because of the need to achieve face recognition in low-light conditions to enable 24-hour …
GW-net: An efficient grad-CAM consistency neural network with weakening of random erasing features for semi-supervised person re-identification
S Zhu, Y Zhang, Y Feng - Image and Vision Computing, 2023 - Elsevier
Person re-identification (Re-ID) subject to loss of detailed information (sacrificing certain
intricate body details) in samples caused by conventional regularization algorithms and …
intricate body details) in samples caused by conventional regularization algorithms and …