Efficient Local Representations of Graphs

2016 ◽  
pp. 83-94
Author(s):  
Edward Scheinerman
Keyword(s):  
Local Representations

Local representations for forward scattering

1972 ◽  
Vol 31 (1-3) ◽  
pp. 273-276
Author(s):  
F. Niedermayer
Keyword(s):  
Forward Scattering ◽  
Local Representations

scholarly journals Multi-granularity Deep Local Representations for Irregular Scene Text Recognition

2021 ◽  
Vol 2 (2) ◽  
pp. 1-18
Author(s):  
Hongchao Gao ◽  
Yujia Li ◽  
Jiao Dai ◽  
Xi Wang ◽  
Jizhong Han ◽  
...  
Keyword(s):  
State Of The Art ◽  
Visual Representation ◽  
Text Recognition ◽  
Natural Scene ◽  
Attention Network ◽  
Training Time ◽  
Scene Text ◽  
Benchmark Datasets ◽  
Local Representations ◽  
Scene Text Recognition

Recognizing irregular text from natural scene images is challenging due to the unconstrained appearance of text, such as curvature, orientation, and distortion. Recent recognition networks regard this task as a text sequence labeling problem and most networks capture the sequence only from a single-granularity visual representation, which to some extent limits the performance of recognition. In this article, we propose a hierarchical attention network to capture multi-granularity deep local representations for recognizing irregular scene text. It consists of several hierarchical attention blocks, and each block contains a Local Visual Representation Module (LVRM) and a Decoder Module (DM). Based on the hierarchical attention network, we propose a scene text recognition network. The extensive experiments show that our proposed network achieves the state-of-the-art performance on several benchmark datasets including IIIT-5K, SVT, CUTE, SVT-Perspective, and ICDAR datasets under shorter training time.

The body and the verb

2020 ◽  
Vol 27 (1) ◽  
pp. 209-239
Author(s):  
Frances Kofod ◽  
Anna Crane
Keyword(s):  
Western Australia ◽  
The Body ◽  
Body Parts ◽  
Expression Of Emotion ◽  
The World ◽  
Physical Impact ◽  
Local Representations ◽  
Australian Languages

Abstract This paper explores the figurative expression of emotion in Gija, a non-Pama-Nyungan language from the East Kimberley in Western Australia. As in many Australian languages, Gija displays a large number of metaphors of emotion where miscellaneous body parts – frequently, the belly – contribute to the figurative representation of emotions. In addition, in Gija certain verbal constructions describe the experience of emotion via metaphors of physical impact or damage. This second profile of metaphors is far less widespread, in Australia and elsewhere in the world, and has also attracted far fewer descriptions. This article explores both types of metaphors in turn. Body-based metaphors will be discussed first, and we will highlight the specificity of Gija in this respect, so as to offer data that can be compared to other languages, in Australia and elsewhere. The second part of the article will present verbal metaphors. Given that this phenomenon is not yet very well undersood, this account aims to take a first step into documenting a previously unexplored domain in the language thereby contributing to the broader typology that this issue forms a part of. Throughout the text, we also endeavour to connect the discussion of metaphors with local representations and understanding of emotions.

scholarly journals Kirillov models for distinguished representations

1989 ◽  
Vol 116 ◽  
pp. 89-110 ◽  
Author(s):  
Courtney Moen
Keyword(s):  
Linear Group ◽  
General Linear Group ◽  
Automorphic Forms ◽  
Principal Series ◽  
Weil Representation ◽  
Local Factors ◽  
Distinguished Representations ◽  
Group A ◽  
Local Representations ◽  
Covering Groups

In the theory of automorphic forms on covering groups of the general linear group, a central role is played by certain local representations which have unique Whittaker models. A representation with this property is called distinguished. In the case of the 2-sheeted cover of GL2, these representations arise as the the local components of generalizations of the classical θ-function. They have been studied thoroughly in [GPS]. The Weil representation provides these representations with a very nice realization, and the local factors attached to these representations can be computed using this realization. It has been shown [KP] that only in the case of a certain 3-sheeted cover do we find other principal series of covering groups of GL2 which have a unique Whittaker model. It is natural to ask if these distinguished representations also have a realization analgous to the Weil representation.

Recognizing Human Actions in Basketball Video Sequences on the Basis of Global and Local Pairwise Representation

2018 ◽  
pp. 2083-2101
Author(s):  
Masaki Takahashi ◽  
Masahide Naemura ◽  
Mahito Fujii ◽  
James J. Little
Keyword(s):  
Feature Representation ◽  
Video Sequences ◽  
Human Actions ◽  
The Public ◽  
Motion Features ◽  
Spatio Temporal ◽  
Representation Method ◽  
Global And Local ◽  
The Relationship ◽  
Local Representations

A feature-representation method for recognizing actions in sports videos on the basis of the relationship between human actions and camera motions is proposed. The method involves the following steps: First, keypoint trajectories are extracted as motion features in spatio-temporal sub-regions called “spatio-temporal multiscale bags” (STMBs). Global representations and local representations from one sub-region in the STMBs are then combined to create a “glocal pairwise representation” (GPR). The GPR considers the co-occurrence of camera motions and human actions. Finally, two-stage SVM classifiers are trained with STMB-based GPRs, and specified human actions in video sequences are identified. An experimental evaluation of the recognition accuracy of the proposed method (by using the public OSUPEL basketball video dataset and broadcast videos) demonstrated that the method can robustly detect specific human actions in both public and broadcast basketball video sequences.

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