Titlebook: Image Analysis; 22nd Scandinavian Co Rikke Gade,Michael Felsberg,Joni-Kristian K?m?r?in Conference proceedings 2023 The Editor(s) (if appli

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鋼盔

CHAD: Charlotte Anomaly Datasetrmine if specific frames of a video contain abnormal behaviors. However, video anomaly detection is particularly context-specific, and the availability of representative datasets heavily limits real-world accuracy. Additionally, the metrics currently reported by most state-of-the-art methods often d

BROOK

iDFD: A Dataset Annotated for?Depth and?Defocusroposed to solve these two tasks separately, using Deep Learning (DL) powerful learning capability. However, when it comes to training the Deep Neural Networks (DNN) for image deblurring or Depth from Defocus (DFD), the mentioned methods are mostly based on synthetic training datasets because of the

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BLAND

Attention-guided Boundary Refinement on?Anchor-free Temporal Action Detectionndencies among features from different temporal locations. Additionally, based on the developed temporal attention unit, we propose an attention-guided boundary refinement module for revising action prediction results. Besides, we integrate the proposed module into a contemporary anchor-free detecto

一美元

Spatio-temporal Attention Graph Convolutions for?Skeleton-based Action Recognitionand the method has achieved excellent results recently. However, GCN-based techniques only focus on the spatial correlations between human joints and often overlook the temporal relationships. In an action sequence, the consecutive frames in a neighborhood contain similar poses and using only tempor

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Directed

To Quantify an?Image Relevance Relative to?a?Target 3D Objectd be both informative and offer a relevant view of the object, .a pose that presents the essential characteristic information about the 3D object. To estimate the quality of the view, we propose to rely on repeatable, second order features, extracted with a curvilinear saliency detector, in order to