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Attribute-wise reasoning reinforcement learning for pedestrian attribute retrieval
Pedestrian attribute retrieval (PAR) aims at retrieving soft-biometric attributes of pedestrian images from video surveillance. Despite advancements,...
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ManiCLIP: Multi-attribute Face Manipulation from Text
In this paper we present a novel multi-attribute face manipulation method based on textual descriptions. Previous text-based image editing methods...
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Attribute subspace-guided multi-scale community detection
Community detection is designed to divide a network into multiple subnetworks (communities) with high cohesiveness, which has attracted wide...
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Graph-based dynamic attribute clip** for conversational recommendation
Conversational recommender systems (CRS) enable traditional recommender systems to interact with users by asking questions about their preferences...
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Attribute- and attention-guided few-shot classification
The field of image classification faces significant challenges due to the scarcity of target samples, leading to model overfitting and difficult...
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Tri-level attribute reduction based on neighborhood rough sets
Tri-level attribute reduction is an interesting topic that aims to reduce the data dimensionality from different levels and granularity perspectives....
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Scattering-based hybrid network for facial attribute classification
Face attribute classification (FAC) is a high-profile problem in biometric verification and face retrieval. Although recent research has been devoted...
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Review: Single attribute and multi attribute facial gender and age estimation
Facial age and gender recognition have vital applications as consumer profile prediction, social media advertisement, human-computer interaction,...
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Disentangled Attribute Features Vision Transformer for Pedestrian Attribute Recognition
Pedestrian attribute recognition, as a sub-task of multi-label classification, is influenced by the joint and coupled relationships among the...
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Pedestrian attribute recognition based on attribute correlation
Pedestrian attribute recognition is widely used in pedestrian tracking and pedestrian re-identification. This task confronts two fundamental...
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Estimation of Near-Instance-Level Attribute Bottleneck for Zero-Shot Learning
Zero-Shot Learning (ZSL) involves transferring knowledge from seen classes to unseen classes by establishing connections between visual and semantic...
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Leakage-Resilient Attribute-Based Encryption with Attribute-Hiding
In this work, we present two generic frameworks for leakage-resilient attribute-based encryption (ABE), which is an improved version of ABE that can...
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Attribute-based document image retrieval
This paper explores the use of attributes for document image querying and retrieval. Existing document image retrieval techniques present several...
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Multi-channel attribute preservation for face de-identification
The advancement of computer vision and surveillance devices has underscored the significance of safeguarding privacy in facial images and videos,...
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A Boolean circuit-based revocable ciphertext policy attribute-based encryption scheme
Attribute-based encryption is a new cryptographic primitive that supports fine-grained access control of cloud data, and its access control function...
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An improved decision tree algorithm based on boundary mixed attribute dependency
As an effective extension of rough set theory, the variable precision neighborhood rough set model has been applied to the attribute dependency-based...
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The granulation attribute reduction of multi-label data
In multi-label learning, the classification obtained by attribute set is usually inconsistent with that based on label set. This makes multi-label...
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WalkNAR: A neighborhood rough sets-based attribute reduction approach using random walk
Neighborhood rough sets, as an effective tool for processing numerical data, is widely used in many fields, such as data mining, machine learning and...
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Attribute augmented and weighted naive Bayes
Numerous enhancements have been proposed to mitigate the attribute conditional independence assumption in naive Bayes (NB). However, almost all of...
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Cluster-based two-branch framework for point cloud attribute compression
Owing to the irregular distribution of point clouds in 3D space, effectively compressing the point cloud is still challenging. Recently, numerous...
