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 "identity aware deep face hallucination via adversarial face verification"):
  Abstract: In this paper, we address the problem of face hallucination by proposing a novel multi-scale generative adversarial network (GAN) architecture optimized for face verification. First, we propose a multi-scale generator architecture for face hallucination with a high up-scaling ratio factor, which has multiple intermediate outputs at different resolutions. The intermediate outputs have the growing goal of synthesizing small to large images. Second, we incorporate a face verifier with the original GAN discriminator and propose a novel discriminator which learns to discriminate different identities while distinguishing fake generated HR face images from their ground truth images. In particular, the learned generator cares for not only the visual quality of hallucinated face images but also preserving the discriminative features in the hallucination process. In addition, to capture perceptually relevant differences we employ a perceptual similarity loss, instead of similarity in pixel space. We perform a quantitative and qualitative evaluation of our framework on the LFW and CelebA datasets. The experimental results show the advantages of our proposed method against the state-of-the-art methods on the 8x downsampled testing dataset.

Includes members:
  Member "using deep cross modal hashing and error correcting codes for improving the efficiency of attribute guided facial image retrieval":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "deep sparse band selection for hyperspectral face recognition")
  Member "sigan siamese generative adversarial network for identity preserving face hallucination":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "subsampling generative adversarial networks density ratio estimation in feature space with softplus loss")
  Member "unsupervised image to image translation using domain specific variational information bound":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "multi level representation learning for deep subspace clustering")
  Member "a deep face identification network enhanced by facial attributes prediction":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "inducing optimal attribute representations for conditional gans")
  Member "style and content disentanglement in generative adversarial networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "sketch to art synthesizing stylized art images from sketches")
  Member "multibiometric secure system based on deep learning":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "segmentation aware and adaptive iris recognition")
  Member "attention aware face hallucination via deep reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "face hallucination with finishing touches")
  Member "biometrics as a service a framework to promote innovative biometric recognition in the cloud":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "deep sparse band selection for hyperspectral face recognition")

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)