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 "guidance and evaluation semantic aware image inpainting for mixed scenes"):
  Abstract: Completing a corrupted image with correct structures and reasonable textures for a mixed scene remains an elusive challenge. Since the missing hole in a mixed scene of a corrupted image often contains various semantic information, conventional two-stage approaches utilizing structural information often lead to the problem of unreliable structural prediction and ambiguous image texture generation. In this paper, we propose a Semantic Guidance and Evaluation Network (SGE-Net) to iteratively update the structural priors and the inpainted image in an interplay framework of semantics extraction and image inpainting. It utilizes semantic segmentation map as guidance in each scale of inpainting, under which location-dependent inferences are re-evaluated, and, accordingly, poorly-inferred regions are refined in subsequent scales. Extensive experiments on real-world images of mixed scenes demonstrated the superiority of our proposed method over state-of-the-art approaches, in terms of clear boundaries and photo-realistic textures.

Includes members:
  Member "learning pyramid context encoder network for high quality image inpainting":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "grounded and controllable image completion by incorporating lexical semantics")
  Member "structureflow image inpainting via structure aware appearance flow":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "deep image spatial transformation for person image generation")
  Member "foreground aware image inpainting":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "fine grained image to image transformation towards visual recognition")
  Member "coherent semantic attention for image inpainting":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "piigan generative adversarial networks for pluralistic image inpainting")
  Member "pluralistic image completion":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "sketch less for more on the fly fine grained sketch based image retrieval")
  Member "semantic image synthesis with spatially adaptive normalization":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "gan compression efficient architectures for interactive conditional gans")
  Member "edgeconnect generative image inpainting with adversarial edge learning":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "piigan generative adversarial networks for pluralistic image inpainting")
  Member "recovering realistic texture in image super resolution by deep spatial feature transform":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "perceptual image super resolution with progressive adversarial network")

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)