Results 51 to 60 of about 167,485 (300)
Relation Network for Person Re-Identification
Proceedings of the AAAI Conference on Artificial Intelligence, 2020 Person re-identification (reID) aims at retrieving an image of the person of interest from a set of images typically captured by multiple cameras. Recent reID methods have shown that exploiting local features describing body parts, together with a global feature of a person image itself, gives robust feature representations, even in the case of missing
Hyunjong Park, Bumsub Ham
openaire +3 more sources
Learning consistent region features for lifelong person re-identification
, 2023 The lifelong person re-identification (LRe-ID) model retrieves a person across multiple cameras in continuous data streams and learns new coming datasets incrementally.
Yaoguang Wei +15 more
core +1 more source
Universal Person Re-Identification
CoRR, 2019 Most state-of-the-art person re-identification (re-id) methods depend on supervised model learning with a large set of cross-view identity labelled training data. Even worse, such trained models are limited to only the same-domain deployment with significantly degraded cross-domain generalization capability, i.e. "domain specific".
Xu Lan, Xiatian Zhu, Shaogang Gong
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A New Model for Person Reidentification Using Deep CNN and Autoencoders [PDF]
Iranica Journal of Energy and Environment, 2023 Person re-identification (re-id) is one of the most critical and challenging topics in image processing and artificial intelligence. In general, person re-identification means that a person seen in the field of view of one camera can be found and tracked
A. Sezavar, H. Farsi, S. Mohamadzadeh
doaj +1 more source
Two‐way constraint network for RGB‐Infrared person re‐identification
Electronics Letters, 2021 RGB‐Infrared person re‐identification (RGB‐IR Re‐ID) is a task aiming to retrieve and match person images between RGB images and IR images. Since most surveillance cameras capture RGB images during the day and IR images at night, RGB‐IR Re‐ID is helpful ...
Haitang Zeng +3 more
doaj +1 more source
Part‐level attention networks for cross‐domain person re‐identification
IET Image Processing, 2021 Person re‐identification (Re‐ID) is in significant demand for intelligent security and single or multiple‐target tracking. However, there are issues in the person Re‐ID tasks, such as sharp decline in cross‐data sets detection accuracy, poor ...
Qun Zhao +9 more
doaj +1 more source
Beyond Triplet Loss: Person Re-identification with Fine-grained Difference-aware Pairwise Loss
, 2021 Person Re-IDentification (ReID) aims at re-identifying persons from different viewpoints across multiple cameras. Capturing the fine-grained appearance differences is often the key to accurate person ReID, because many identities can be differentiated ...
Yan, C +6 more
core +1 more source
Human-in-the-Loop Person Re-identification [PDF]
, 2016 Current person re-identification (re-id) methods assume that (1) pre-labelled training data are available for every camera pair, (2) the gallery size for re-identification is moderate. Both assumptions scale poorly to real-world applications when camera network size increases and gallery size becomes large.
Hanxiao Wang 0001 +3 more
openaire +2 more sources
Agent-based framework for person re-identification [PDF]
, 2017 In computer based human object re-identification, a detected human is recognised to a level sufficient to re-identify a tracked person in either a different camera capturing the same individual, often at a different angle, or the same camera at a ...
Muna S. Al-Rahbi (7168118)
core +1 more source
Identity Adaptation for Person Re-Identification
IEEE Access, 2018 Person re-identification (re-ID), which aims to identify the same individual from a gallery collected with different cameras, has attracted increasing attention in the multimedia retrieval community.
Qiuhong Ke +5 more
doaj +1 more source