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 "high resolution deep convolutional generative adversarial networks"):
  Abstract: Generative Adversarial Networks (GANs) convergence in a high-resolution setting with a computational constrain of GPU memory capacity (from 12GB to 24 GB) has been beset with difficulty due to the known lack of convergence rate stability. In order to boost network convergence of DCGAN (Deep Convolutional Generative Adversarial Networks) and achieve good-looking high-resolution results we propose a new layered network structure, HR-DCGAN, that incorporates current state-of-the-art techniques for this effect. A novel dataset, CZ Faces (CZF), containing human faces from different ethnical groups in a wide variety of illumination conditions and image resolutions is introduced. We conduct extensive experiments on CelebA and CZF.

Includes members:
  Member "video to video synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "gan compression efficient architectures for interactive conditional gans")
  Member "faceshop deep sketch based face image editing":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "deep plastic surgery robust and controllable image editing with human drawn sketches")
  Member "improving the improved training of wasserstein gans a consistency term and its dual effect":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "sliced wasserstein generative models")
  Member "smit stochastic multi label image to image translation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "stargan v2 diverse image synthesis for multiple domains")
  Member "large scale gan training for high fidelity natural image synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "generative adversarial networks in computer vision a survey and taxonomy")
  Member "learning semantic segmentation from synthetic data a geometrically guided input output adaptation approach":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "cars can t fly up in the sky improving urban scene segmentation via height driven attention networks")
  Member "deep appearance models for face rendering":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "neural human video rendering joint learning of dynamic textures and rendering to video translation")
  Member "which training methods for gans do actually converge":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a novel framework for selection of gans for an application")

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)