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Detecting texts of arbitrary orientations in natural images
With the increasing popularity of practical vision systems and smart phones, text detection in natural scenes becomes a critical yet challenging task. Most existing methods have focused on detectingExpand
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CosFace: Large Margin Cosine Loss for Deep Face Recognition
  • H. Wang, Yitong Wang, +5 authors Wenyu Liu
  • Computer Science
  • IEEE/CVF Conference on Computer Vision and…
  • 29 January 2018
Face recognition has made extraordinary progress owing to the advancement of deep convolutional neural networks (CNNs). The central task of face recognition, including face verification andExpand
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TextBoxes: A Fast Text Detector with a Single Deep Neural Network
This paper presents an end-to-end trainable fast scene text detector, named TextBoxes, which detects scene text with both high accuracy and efficiency in a single network forward pass, involving noExpand
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Multiple Instance Detection Network with Online Instance Classifier Refinement
Of late, weakly supervised object detection is with great importance in object recognition. Based on deep learning, weakly supervised detectors have achieved many promising results. However, comparedExpand
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Skeleton Pruning by Contour Partitioning with Discrete Curve Evolution
In this paper, we introduce a new skeleton pruning method based on contour partitioning. Any contour partition can be used, but the partitions obtained by discrete curve evolution (DCE) yieldExpand
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Mining user similarity based on location history
The pervasiveness of location-acquisition technologies (GPS, GSM networks, etc.) enable people to conveniently log the location histories they visited with spatio-temporal data. The increasingExpand
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Minimizing Electricity Cost: Optimization of Distributed Internet Data Centers in a Multi-Electricity-Market Environment
The study of Cyber-Physical System (CPS) has been an active area of research. Internet Data Center (IDC) is an important emerging Cyber-Physical System. As the demand on Internet services drasticallyExpand
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Mancs: A Multi-task Attentional Network with Curriculum Sampling for Person Re-Identification
We propose a novel deep network called Mancs that solves the person re-identification problem from the following aspects: fully utilizing the attention mechanism for the person misalignment problemExpand
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Weakly-Supervised Semantic Segmentation Network with Deep Seeded Region Growing
This paper studies the problem of learning image semantic segmentation networks only using image-level labels as supervision, which is important since it can significantly reduce human annotationExpand
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PCL: Proposal Cluster Learning for Weakly Supervised Object Detection
Weakly Supervised Object Detection (WSOD), using only image-level annotations to train object detectors, is of growing importance in object recognition. In this paper, we propose a novel deep networkExpand
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