About: Mask-Guided Region Attention Network for Person Re-Identification

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Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Mask-Guided Region Attention Network for Person Re-Identification
Creator	Yu, Han Zhou, Cong
Source	PMC
abstract	Person re-identification (ReID) is an important and practical task which identifies pedestrians across non-overlapping surveillance cameras based on their visual features. In general, ReID is an extremely challenging task due to complex background clutters, large pose variations and severe occlusions. To improve its performance, a robust and discriminative feature extraction methodology is particularly crucial. Recently, the feature alignment technique driven by human pose estimation, that is, matching two person images with their corresponding parts, increases the effectiveness of ReID to a certain extent. However, we argue that there are still a few problems among these methods such as imprecise handcrafted segmentation of body parts, and some improvements can be further achieved. In this paper, we present a novel framework called Mask-Guided Region Attention Network (MGRAN) for person ReID. MGRAN consists of two major components: Mask-guided Region Attention (MRA) and Multi-feature Alignment (MA). MRA aims to generate spatial attention masks and meanwhile mask out the background clutters and occlusions. Moreover, the generated masks are utilized for region-level feature alignment in the MA module. We then evaluate the proposed method on three public datasets, including Market-1501, DukeMTMC-reID and CUHK03. Extensive experiments with ablation analysis show the effectiveness of this method.
has issue date	2020-04-17(xsd:dateTime)
bibo:doi	10.1007/978-3-030-47436-2_22
has license	no-cc
sha1sum (hex)	92164ea3e8136496345c46694bed0a4f57d95f6f
schema:url	https://doi.org/10.1007/978-3-030-47436-2_22
resource representing a document's title	Mask-Guided Region Attention Network for Person Re-Identification
has PubMed Central identifier	PMC7206236
schema:publication	Advances in Knowledge Discovery and Data Mining
resource representing a document's body	covid:92164ea3e8136496345c46694bed0a4f57d95f6f#body_text
is schema:about of	named entity 'features' named entity 'estimation' named entity 'images' named entity 'These' named entity 'segmentation' named entity 'Attention' named entity 'pose estimation' named entity 'driven' named entity 'surveillance cameras' named entity 'success' named entity 'MRA' named entity 'Region' named entity 'identifies' named entity 'argue' named entity 'consists' named entity 'body parts' named entity 'extremely' named entity 'null space' named entity 'one-hot' named entity 'image retrieval' named entity 'distance metric' named entity 'pixel' named entity 'metric learning' named entity 'neural network' named entity 'CNN' named entity 'neural network' named entity 'cross-entropy' named entity 'CNN' named entity 'deep learning' named entity 'feature vectors' named entity 'ResNet' named entity 'human pose estimation' named entity 'feature vector' named entity 'ResNet' named entity 'semi-supervised learning' named entity 'human pose estimation' named entity 'MSML' named entity 'ResNet' named entity 'transfer learning' named entity 'softmax' named entity 'Hadamard Product' named entity 'CNN' named entity 'ground truth' named entity 'deep learning' named entity 'sigmoid function' named entity 'convolution' named entity 'pose estimation' named entity 'pixel' named entity 'CNN' named entity 'ResNet' named entity 'CNN' named entity 'CNN' named entity 'object detection' named entity 'cross-entropy' named entity 'Hadamard Product' named entity 'DLPAR' named entity 'pixel' named entity 'ResNet' named entity 'Hadamard Product' named entity 'metric learning' named entity 'reduce the noise' named entity 'feature vectors' named entity 'major components' named entity 'surveillance cameras' named entity 'However' named entity 'Network' named entity 'METHODOLOGY' named entity 'PERSON RE-IDENTIFICATION' named entity 'ITS' named entity 'SEVERE' named entity 'CERTAIN' covid:arg/92164ea3e8136496345c46694bed0a4f57d95f6f named entity 'public datasets' named entity 'feature extraction' named entity 'ALIGN' named entity 'PRESENT' named entity 'MAPS' named entity 'PROBLEMS' named entity 'SUCCESS' named entity 'DUE TO' named entity 'ALIGNMENT' named entity 'GENERATE'

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