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 "imitation learning for human pose prediction"):
  Abstract: Modeling and prediction of human motion dynamics has long been a challenging problem in computer vision, and most existing methods rely on the end-to-end supervised training of various architectures of recurrent neural networks. Inspired by the recent success of deep reinforcement learning methods, in this paper we propose a new reinforcement learning formulation for the problem of human pose prediction, and develop an imitation learning algorithm for predicting future poses under this formulation through a combination of behavioral cloning and generative adversarial imitation learning. Our experiments show that our proposed method outperforms all existing state-of-the-art baseline models by large margins on the task of human pose prediction in both short-term predictions and long-term predictions, while also enjoying huge advantage in training speed.

Includes members:
  Member "procedure planning in instructional videos":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "video2commonsense generating commonsense descriptions to enrich video captioning")
  Member "peeking into the future predicting future person activities and locations in videos":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "social wagdat interaction aware trajectory prediction via wasserstein graph double attention network")
  Member "mt vae learning motion transformations to generate multimodal human dynamics":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "dlow diversifying latent flows for diverse human motion prediction")
  Member "action agnostic human pose forecasting":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "dlow diversifying latent flows for diverse human motion prediction")
  Member "deepmimic example guided deep reinforcement learning of physics based character skills":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "artificial intelligence for prosthetics challenge solutions")
  Member "learning plannable representations with causal infogan":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "probabilistic future prediction for video scene understanding")
  Member "predicting deeper into the future of semantic segmentation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "transformation based adversarial video prediction on large scale data")
  Member "hp gan probabilistic 3d human motion prediction via gan":
    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)