Occluded person re-identification with deep learning: a survey and perspectives
Person re-identification (Re-ID) technology plays an increasingly crucial role in intelligent
surveillance systems. Widespread occlusion significantly impacts the performance of person …
surveillance systems. Widespread occlusion significantly impacts the performance of person …
Part-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 …
for person retrieval from unlabeled data. Recent techniques accomplish this task by using …
Fmcnet: Feature-level modality compensation for visible-infrared person re-identification
Abstract For Visible-Infrared person Re-IDentification (VI-ReID), existing modality-specific
information compensation based models try to generate the images of missing modality from …
information compensation based models try to generate the images of missing modality from …
Transreid: Transformer-based object re-identification
Extracting robust feature representation is one of the key challenges in object re-
identification (ReID). Although convolution neural network (CNN)-based methods have …
identification (ReID). Although convolution neural network (CNN)-based methods have …
Diverse part discovery: Occluded person re-identification with part-aware transformer
Occluded person re-identification (Re-ID) is a challenging task as persons are frequently
occluded by various obstacles or other persons, especially in the crowd scenario. To …
occluded by various obstacles or other persons, especially in the crowd scenario. To …
Dual cross-attention learning for fine-grained visual categorization and object re-identification
Recently, self-attention mechanisms have shown impressive performance in various NLP
and CV tasks, which can help capture sequential characteristics and derive global …
and CV tasks, which can help capture sequential characteristics and derive global …
Counterfactual attention learning for fine-grained visual categorization and re-identification
Attention mechanism has demonstrated great potential in fine-grained visual recognition
tasks. In this paper, we present a counterfactual attention learning method to learn more …
tasks. In this paper, we present a counterfactual attention learning method to learn more …
Clothes-changing person re-identification with rgb modality only
The key to address clothes-changing person re-identification (re-id) is to extract clothes-
irrelevant features, eg, face, hairstyle, body shape, and gait. Most current works mainly focus …
irrelevant features, eg, face, hairstyle, body shape, and gait. Most current works mainly focus …
Nformer: Robust person re-identification with neighbor transformer
Person re-identification aims to retrieve persons in highly varying settings across different
cameras and scenarios, in which robust and discriminative representation learning is …
cameras and scenarios, in which robust and discriminative representation learning is …