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 "domain embedded multi model generative adversarial networks for image based face inpainting"):
  Abstract: Prior knowledge of face shape and location plays an important role in face inpainting. However, traditional facing inpainting methods mainly focus on the generated image resolution of the missing portion but without consideration of the special particularities of the human face explicitly and generally produce discordant facial parts. To solve this problem, we present a stable variational latent generative model for large inpainting of face images. We firstly represent only face regions with the latent variable space but simultaneously constraint the random vectors to offer control over the distribution of latent variables, and combine with the non-face parts textures to generate a face image with plausible contents. Two adversarial discriminators are finally used to judge whether the generated distribution is close to the real distribution or not. It can not only synthesize novel image structures but also explicitly utilize the latent space with Eigenfaces to make better predictions. Furthermore, our work better evaluates the side face impainting problem. Experiments on both CelebA and CelebA-HQ face datasets demonstrate that our proposed approach generates higher quality inpainting results than existing ones.

Includes members:
  Member "image inpainting with learnable bidirectional attention maps":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "vcnet a robust approach to blind image inpainting")
  Member "deep fusion network for image completion":
    also connected through other hyperedges:
      (none)
  Member "learning pyramid context encoder network for high quality image inpainting":
    also connected through other hyperedges:
      - Hyperedge HE-2 (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-3 (induced by source paper "deep image spatial transformation for person image generation")
  Member "foreground aware image inpainting":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "fine grained image to image transformation towards visual recognition")
  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 "alphagan generative adversarial networks for natural image matting":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "natural image matting via guided contextual attention")
  Member "semantic image inpainting through improved wasserstein generative adversarial networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "local facial attribute transfer through inpainting")

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)