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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 …
A survey of human gait-based artificial intelligence applications
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 …
Deepchange: A long-term person re-identification benchmark with clothes change
Long-term re-id with clothes change is a challenging problem in surveillance AI. Currently,
its major bottleneck is that this field is still missing a large realistic benchmark. In this work …
its major bottleneck is that this field is still missing a large realistic benchmark. In this work …
Beyond part models: Person retrieval with refined part pooling (and a strong convolutional baseline)
Employing part-level features offers fine-grained information for pedestrian image
description. A prerequisite of part discovery is that each part should be well located. Instead …
description. A prerequisite of part discovery is that each part should be well located. Instead …
Person transfer gan to bridge domain gap for person re-identification
Although the performance of person Re-Identification (ReID) has been significantly boosted,
many challenging issues in real scenarios have not been fully investigated, eg, the complex …
many challenging issues in real scenarios have not been fully investigated, eg, the complex …
Cityflow: A city-scale benchmark for multi-target multi-camera vehicle tracking and re-identification
Urban traffic optimization using traffic cameras as sensors is driving the need to advance
state-of-the-art multi-target multi-camera (MTMC) tracking. This work introduces CityFlow, a …
state-of-the-art multi-target multi-camera (MTMC) tracking. This work introduces CityFlow, a …
Features for multi-target multi-camera tracking and re-identification
Abstract Multi-Target Multi-Camera Tracking (MTMCT) tracks many people through video
taken from several cameras. Person Re-Identification (Re-ID) retrieves from a gallery images …
taken from several cameras. Person Re-Identification (Re-ID) retrieves from a gallery images …
Part-aligned bilinear representations for person re-identification
Comparing the appearance of corresponding body parts is essential for person re-
identification. As body parts are frequently misaligned between the detected human boxes …
identification. As body parts are frequently misaligned between the detected human boxes …
Transferable joint attribute-identity deep learning for unsupervised person re-identification
Most existing person re-identification (re-id) methods require supervised model learning
from a separate large set of pairwise labelled training data for every single camera pair. This …
from a separate large set of pairwise labelled training data for every single camera pair. This …
Pose-driven deep convolutional model for person re-identification
Feature extraction and matching are two crucial components in person Re-Identification
(ReID). The large pose deformations and the complex view variations exhibited by the …
(ReID). The large pose deformations and the complex view variations exhibited by the …