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 music driven dance generation using wavenet"):
  Abstract: In this paper, we propose a novel system, named as Music2Dance, for addressing the problem of fully automatic music and choreography. Our key idea is to shift the WaveNet, which is originally designed for speech generation, to the human motion synthesis. To balance the big differences between these two tasks, we propose a novel network structure. Typically, being regarded as the local condition for our network, the music features are first extracted by considering the characteristics of rhythms and melody. In addition, the types of dance are then designed as the global condition for the network. Both of the two conditions are utilized to stabilize the network training. Beyond the network architecture, another main challenge is the lack of data. In order to further tackle the obstacle, we have captured the synchronized music-dance pairs by professional dancers, and thus build a high-quality music-dance pair dataset. Experiments have demonstrated the performance of the proposed system and the proposed method can achieve the state-of-the-art results.

Includes members:
  Member "a neural temporal model for human motion prediction":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "dlow diversifying latent flows for diverse human motion prediction")
  Member "openpose realtime multi person 2d pose estimation using part affinity fields":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the state of service robots current bottlenecks in object perception and manipulation")
  Member "listen to dance music driven choreography generation using autoregressive encoder decoder network":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "music2dance dancenet for music driven dance generation")
  Member "neural kinematic networks for unsupervised motion retargetting":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "do as i do transferring human motion and appearance between monocular videos with spatial and temporal constraints")
  Member "weakly supervised deep recurrent neural networks for basic dance step generation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "music2dance dancenet for music driven dance generation")
  Member "onsets and frames dual objective piano transcription":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "music2dance dancenet for music driven dance generation")
  Member "on human motion prediction using recurrent neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "dlow diversifying latent flows for diverse human motion prediction")
  Member "auto conditioned recurrent networks for extended complex human motion synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "dlow diversifying latent flows for diverse human motion prediction")

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)