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 "emerging applications of reversible data hiding"):
  Abstract: Reversible data hiding (RDH) is one special type of information hiding, by which the host sequence as well as the embedded data can be both restored from the marked sequence without loss. Beside media annotation and integrity authentication, recently some scholars begin to apply RDH in many other fields innovatively. In this paper, we summarize these emerging applications, including steganography, adversarial example, visual transformation, image processing, and give out the general frameworks to make these operations reversible. As far as we are concerned, this is the first paper to summarize the extended applications of RDH.

Includes members:
  Member "stereoscopic neural style transfer":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "style transfer for light field photography")
  Member "deep exemplar based colorization":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "chromagan adversarial picture colorization with semantic class distribution")
  Member "decouple learning for parameterized image operators":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "meta sr a magnification arbitrary network for super resolution")
  Member "stylebank an explicit representation for neural image style transfer":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "collaborative distillation for ultra resolution universal style transfer")
  Member "coherent online video style transfer":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "perception and decision making of autonomous systems in the era of learning an overview")
  Member "learning representations for automatic colorization":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "learning representations by predicting bags of visual words")
  Member "texture synthesis using convolutional neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "collaborative distillation for ultra resolution universal style transfer")

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)