Deep learning for person re-identification: A survey and outlook
Person re-identification (Re-ID) aims at retrieving a person of interest across multiple non-
overlapping cameras. With the advancement of deep neural networks and increasing …
overlapping cameras. With the advancement of deep neural networks and increasing …
A survey of human gait-based artificial intelligence applications
EJ Harris, IH Khoo, E Demircan - Frontiers in Robotics and AI, 2022 - frontiersin.org
We performed an electronic database search of published works from 2012 to mid-2021 that
focus on human gait studies and apply machine learning techniques. We identified six key …
focus on human gait studies and apply machine learning techniques. We identified six key …
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 …
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 …
Shape-erased feature learning for visible-infrared person re-identification
Due to the modality gap between visible and infrared images with high visual ambiguity,
learning diverse modality-shared semantic concepts for visible-infrared person re …
learning diverse modality-shared semantic concepts for visible-infrared person re …
Identity-guided human semantic parsing for person re-identification
Existing alignment-based methods have to employ the pre-trained human parsing models to
achieve the pixel-level alignment, and cannot identify the personal belongings (eg …
achieve the pixel-level alignment, and cannot identify the personal belongings (eg …
Omni-scale feature learning for person re-identification
As an instance-level recognition problem, person re-identification (ReID) relies on
discriminative features, which not only capture different spatial scales but also encapsulate …
discriminative features, which not only capture different spatial scales but also encapsulate …
High-order information matters: Learning relation and topology for occluded person re-identification
Occluded person re-identification (ReID) aims to match occluded person images to holistic
ones across dis-joint cameras. In this paper, we propose a novel framework by learning high …
ones across dis-joint cameras. In this paper, we propose a novel framework by learning high …
Abd-net: Attentive but diverse person re-identification
Attention mechanisms have been found effective for person re-identification (Re-ID).
However, the learned" attentive" features are often not naturally uncorrelated or" diverse" …
However, the learned" attentive" features are often not naturally uncorrelated or" diverse" …
Feature refinement and filter network for person re-identification
In the task of person re-identification, the attention mechanism and fine-grained information
have been proved to be effective. However, it has been observed that models often focus on …
have been proved to be effective. However, it has been observed that models often focus on …