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 "music2dance dancenet for music driven dance generation"):
  Abstract: Synthesize human motions from music, i.e., music to dance, is appealing and attracts lots of research interests in recent years. It is challenging due to not only the requirement of realistic and complex human motions for dance, but more importantly, the synthesized motions should be consistent with the style, rhythm and melody of the music. In this paper, we propose a novel autoregressive generative model, DanceNet, to take the style, rhythm and melody of music as the control signals to generate 3D dance motions with high realism and diversity. To boost the performance of our proposed model, we capture several synchronized music-dance pairs by professional dancers, and build a high-quality music-dance pair dataset. Experiments have demonstrated that the proposed method can achieve the state-of-the-art results.

Includes members:
  Member "dancing to music":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "neural design network graphic layout generation with constraints")
  Member "learning individual styles of conversational gesture":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "unsupervised any to many audiovisual synthesis via exemplar autoencoders")
  Member "a neural temporal model for human motion prediction":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "dlow diversifying latent flows for diverse human motion prediction")
  Member "listen to dance music driven choreography generation using autoregressive encoder decoder network":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "music2dance music driven dance generation using wavenet")
  Member "convolutional sequence to sequence model for human dynamics":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "dynamic multiscale graph neural networks for 3d skeleton based human motion prediction")
  Member "3d human pose estimation in video with temporal convolutions and semi supervised training":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "posenet3d unsupervised 3d human shape and pose estimation")
  Member "weakly supervised deep recurrent neural networks for basic dance step generation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "music2dance music driven dance generation using wavenet")
  Member "onsets and frames dual objective piano transcription":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "music2dance music driven dance generation using wavenet")

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)