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 "audio driven talking face video generation with natural head pose"):
  Abstract: Real-world talking faces often accompany with natural head movement. However, most existing talking face video generation methods only consider facial animation with fixed head pose. In this paper, we address this problem by proposing a deep neural network model that takes an audio signal A of a source person and a very short video V of a target person as input, and outputs a synthesized high-quality talking face video with natural head pose (making use of the visual information in V), expression and lip synchronization (by considering both A and V). The most challenging issue in our work is that natural poses often cause in-plane and out-of-plane head rotations, which makes synthesized talking face video far from realistic. To address this challenge, we reconstruct 3D face animation and re-render it into synthesized frames. To fine tune these frames into realistic ones with smooth background transition, we propose a novel memory-augmented GAN module. Extensive experiments and three user studies show that our method can generate high-quality (i.e., natural head movements, expressions and good lip synchronization) personalized talking face videos, outperforming the state-of-the-art methods.

Includes members:
  Member "coloring with limited data few shot colorization via memory augmented networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "audio driven talking face video generation with learning based personalized head pose")
  Member "few shot adversarial learning of realistic neural talking head models":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "opengan open set generative adversarial networks")
  Member "one shot face reenactment":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "audio driven talking face video generation with learning based personalized head pose")
  Member "accurate 3d face reconstruction with weakly supervised learning from single image to image set":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "audio driven talking face video generation with learning based personalized head pose")
  Member "speech2face learning the face behind a voice":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "audio driven talking face video generation with learning based personalized head pose")
  Member "video to video synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "gan compression efficient architectures for interactive conditional gans")
  Member "abstractive summarization of reddit posts with multi level memory networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "audio driven talking face video generation with learning based personalized head pose")
  Member "talking face generation by adversarially disentangled audio visual representation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "rotate and render unsupervised photorealistic face rotation from single view images")

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)