human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "fake generated painting detection via frequency analysis"):
  Abstract: With the development of deep neural networks, digital fake paintings can be generated by various style transfer algorithms.To detect the fake generated paintings, we analyze the fake generated and real paintings in Fourier frequency domain and observe statistical differences and artifacts. Based on our observations, we propose Fake Generated Painting Detection via Frequency Analysis (FGPD-FA) by extracting three types of features in frequency domain. Besides, we also propose a digital fake painting detection database for assessing the proposed method. Experimental results demonstrate the excellence of the proposed method in different testing conditions.

Includes members:
  Member "face x ray for more general face forgery detection":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "fakelocator robust localization of gan based face manipulations via semantic segmentation networks with bells and whistles")
  Member "attention aware multi stroke style transfer":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "p 2 gan efficient style transfer using single style image")
  Member "gated gan adversarial gated networks for multi collection style transfer":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "p 2 gan efficient style transfer using single style image")
  Member "distinguishing computer generated graphics from natural images based on sensor pattern noise and deep learning":
    also connected through other hyperedges:
      (none)
  Member "fake colorized image detection":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "detecting colorized images via convolutional neural networks toward high accuracy and good generalization")
  Member "do gans leave artificial fingerprints":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "global texture enhancement for fake face detection in the wild")
  Member "detection of deep network generated images using disparities in color components":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "global texture enhancement for fake face detection in the wild")
  Member "learning to discover cross domain relations with generative adversarial networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "gan compression efficient architectures for interactive conditional gans")

Question: Please tell me which class the source paper 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)