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 "dual reference age synthesis"):
  Abstract: Age synthesis has received much attention in recent years. State-of-the-art methods typically take an input image and utilize a numeral to control the age of the generated image. In this paper, we revisit the age synthesis and ask: is a numeral capable enough to describe the human age? We propose a new framework Dual-reference Age Synthesis (DRAS) that takes two images as inputs to generate an image which shares the same personality of the first image and has the similar age with the second image. In the proposed framework, we employ a joint manifold feature which consists of disentangled age and identity information. The final images are generated by training a generative adversarial network which competes against an age agent and an identity agent. Experimental results demonstrate the appealing performance and flexibility of the proposed framework by comparing with the state-of-the-art and ground truth.

Includes members:
  Member "face aging with contextual generative adversarial nets":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "ugan untraceable gan for multi domain face translation")
  Member "face aging with conditional generative adversarial networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "algorithmic fairness")
  Member "exprgan facial expression editing with controllable expression intensity":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "inducing optimal attribute representations for conditional gans")
  Member "learning face age progression a pyramid architecture of gans":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "child face age progression via deep feature aging")
  Member "age progression regression by conditional adversarial autoencoder":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "nestedvae isolating common factors via weak supervision")
  Member "stargan unified generative adversarial networks for multi domain image to image translation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "generative adversarial networks in computer vision a survey and taxonomy")
  Member "photo realistic facial texture transfer":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "semi supervised learning for face sketch synthesis in the wild")
  Member "fader networks manipulating images by sliding attributes":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "deepfakes and beyond a survey of face manipulation and fake detection")

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)