Multi-task learning with coarse priors for robust part-aware person re-identification
Part-level representations are important for robust person re-identification (ReID), but in
practice feature quality suffers due to the body part misalignment problem. In this paper, we …
practice feature quality suffers due to the body part misalignment problem. In this paper, we …
Horeid: deep high-order mapping enhances pose alignment for person re-identification
P Wang, Z Zhao, F Su, X Zu… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Despite the remarkable progress in recent years, person Re-Identification (ReID)
approaches frequently fail in cases where the semantic body parts are misaligned between …
approaches frequently fail in cases where the semantic body parts are misaligned between …
Autolr: Layer-wise pruning and auto-tuning of learning rates in fine-tuning of deep networks
Existing fine-tuning methods use a single learning rate over all layers. In this paper, first, we
discuss that trends of layer-wise weight variations by fine-tuning using a single learning rate …
discuss that trends of layer-wise weight variations by fine-tuning using a single learning rate …
Person re-identification with part prediction alignment
Z Li, J Lv, Y Chen, J Yuan - Computer Vision and Image Understanding, 2021 - Elsevier
The key to success of person re-identification (re-id) is extracting the discriminative person
features. Various part-level feature extraction methods are proposed to capture local person …
features. Various part-level feature extraction methods are proposed to capture local person …
ReFine: Re-randomization before Fine-tuning for Cross-domain Few-shot Learning
Cross-domain few-shot learning (CD-FSL), where there are few target samples under
extreme differences between source and target domains, has recently attracted huge …
extreme differences between source and target domains, has recently attracted huge …
[HTML][HTML] Multi-view feature fusion for person re-identification
Person re-identification (ReID) suffers from camera view variants. Existing works, which
typically learn a feature for each image, share a limitation that the learned features are …
typically learn a feature for each image, share a limitation that the learned features are …
Multi-modal context propagation for person re-identification with wireless positioning
Existing person re-identification methods mainly rely on the visual appearance captured by
cameras for identity matching. However, dueto the sensitivity of visual data to occlusion, blur …
cameras for identity matching. However, dueto the sensitivity of visual data to occlusion, blur …
Learning hybrid relationships for person re-identification
Recently, the relationship among individual pedestrian images and the relationship among
pairwise pedestrian images have become attractive for person re-identification (re-ID) as …
pairwise pedestrian images have become attractive for person re-identification (re-ID) as …
Exploring cross-modality commonalities via dual-stream multi-branch network for infrared-visible person re-identification
D Cheng, X Li, M Qi, X Liu, C Chen, D Niu - IEEE access, 2020 - ieeexplore.ieee.org
Infrared-Visible person Re-IDentification (IV-ReID) is an emerging subject, which has
important research significance for nighttime monitoring. Existing works focus on reducing …
important research significance for nighttime monitoring. Existing works focus on reducing …
Development of decision support software for deep learning-based automated retinal disease screening using relatively limited fundus photograph data
Purpose—This study was conducted to develop an automated detection algorithm for
screening fundus abnormalities, including age-related macular degeneration (AMD) …
screening fundus abnormalities, including age-related macular degeneration (AMD) …