human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "accurate scene text detection through border semantics awareness and bootstrapping"
  Abstract: This paper presents a scene text detection technique that exploits bootstrapping and text border semantics for accurate localization of texts in scenes. A novel bootstrapping technique is designed which samples multiple 'subsections' of a word or text line and accordingly relieves the constraint of limited training data effectively. At the same time, the repeated sampling of text 'subsections' improves the consistency of the predicted text feature maps which is critical in predicting a single complete instead of multiple broken boxes for long words or text lines. In addition, a semantics-aware text border detection technique is designed which produces four types of text border segments for each scene text. With semantics-aware text borders, scene texts can be localized more accurately by regressing text pixels around the ends of words or text lines instead of all text pixels which often leads to inaccurate localization while dealing with long words or text lines. Extensive experiments demonstrate the effectiveness of the proposed techniques, and superior performance is obtained over several public datasets, e. g. 80.1 f-score for the MSRA-TD500, 67.1 f-score for the ICDAR2017-RCTW, etc.

Connected through hyperedge HE-1 (induced by source paper "deep relational reasoning graph network for arbitrary shape text detection"):
  with members:
    - "arbitrary shape scene text detection with adaptive text region representation"
    - "look more than once an accurate detector for text of arbitrary shapes"
    - "textfield learning a deep direction field for irregular scene text detection"
    - "character region awareness for text detection"
    - "linkage based face clustering via graph convolution network"
    - "msr multi scale shape regression for scene text detection"
    - "efficient and accurate arbitrary shaped text detection with pixel aggregation network"
    - "towards robust curve text detection with conditional spatial expansion"

Connected through hyperedge HE-2 (induced by source paper "text perceptron towards end to end arbitrary shaped text spotting"):
  with members:
    - "look more than once an accurate detector for text of arbitrary shapes"
    - "textfield learning a deep direction field for irregular scene text detection"
    - "towards robust curve text detection with conditional spatial expansion"
    - "shape robust text detection with progressive scale expansion network"
    - "arbitrary oriented scene text detection via rotation proposals"
    - "fots fast oriented text spotting with a unified network"
    - "an end to end textspotter with explicit alignment and attention"
    - "textsnake a flexible representation for detecting text of arbitrary shapes"

Connected through hyperedge HE-3 (induced by source paper "exploring the capacity of sequential free box discretization network for omnidirectional scene text detection"):
  with members:
    - "arbitrary shape scene text detection with adaptive text region representation"
    - "look more than once an accurate detector for text of arbitrary shapes"
    - "textfield learning a deep direction field for irregular scene text detection"
    - "omnidirectional scene text detection with sequential free box discretization"
    - "character region awareness for text detection"
    - "region proposal by guided anchoring"
    - "msr multi scale shape regression for scene text detection"
    - "mask scoring r cnn"

Connected through hyperedge HE-4 (induced by source paper "ga dan geometry aware domain adaptation network for scene text detection and recognition"):
  with members:
    - "adaptive composition gan towards realistic image synthesis"
    - "scene text synthesis for efficient and effective deep network training"
    - "rotation sensitive regression for oriented scene text detection"
    - "st gan spatial transformer generative adversarial networks for image compositing"
    - "fots fast oriented text spotting with a unified network"
    - "textsnake a flexible representation for detecting text of arbitrary shapes"
    - "pixellink detecting scene text via instance segmentation"
    - "verisimilar image synthesis for accurate detection and recognition of texts in scenes"

Connected through hyperedge HE-5 (induced by source paper "textfield learning a deep direction field for irregular scene text detection"):
  with members:
    - "rotation sensitive regression for oriented scene text detection"
    - "arbitrary oriented scene text detection via rotation proposals"
    - "an end to end textspotter with explicit alignment and attention"
    - "verisimilar image synthesis for accurate detection and recognition of texts in scenes"
    - "deepflux for skeletons in the wild"
    - "textboxes a single shot oriented scene text detector"
    - "learning markov clustering networks for scene text detection"
    - "multi oriented scene text detection via corner localization and region segmentation"

Connected through hyperedge HE-6 (induced by source paper "gliding vertex on the horizontal bounding box for multi oriented object detection"):
  with members:
    - "arbitrary shape scene text detection with adaptive text region representation"
    - "look more than once an accurate detector for text of arbitrary shapes"
    - "textfield learning a deep direction field for irregular scene text detection"
    - "centernet keypoint triplets for object detection"
    - "cad net a context aware detection network for objects in remote sensing imagery"
    - "bottom up object detection by grouping extreme and center points"
    - "cornernet detecting objects as paired keypoints"
    - "rotation sensitive regression for oriented scene text detection"

Connected through hyperedge HE-7 (induced by source paper "texttubes for detecting curved text in the wild"):
  with members:
    - "inceptext a new inception text module with deformable psroi pooling for multi oriented scene text detection"
    - "arbitrary oriented scene text detection via rotation proposals"
    - "fots fast oriented text spotting with a unified network"
    - "textsnake a flexible representation for detecting text of arbitrary shapes"
    - "pixellink detecting scene text via instance segmentation"
    - "sliding line point regression for shape robust scene text detection"
    - "textboxes a single shot oriented scene text detector"
    - "the open images dataset v4 unified image classification object detection and visual relationship detection at scale"

Connected through hyperedge HE-8 (induced by source paper "look more than once an accurate detector for text of arbitrary shapes"):
  with members:
    - "inceptext a new inception text module with deformable psroi pooling for multi oriented scene text detection"
    - "shape robust text detection with progressive scale expansion network"
    - "arbitrary oriented scene text detection via rotation proposals"
    - "fots fast oriented text spotting with a unified network"
    - "textsnake a flexible representation for detecting text of arbitrary shapes"
    - "pixellink detecting scene text via instance segmentation"
    - "sliding line point regression for shape robust scene text detection"
    - "e2e mlt an unconstrained end to end method for multi language scene text"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.CV(Computer Vision and Pattern Recognition)