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 "street scene a new dataset and evaluation protocol for video anomaly detection"):
  Abstract: Progress in video anomaly detection research is currently slowed by small datasets that lack a wide variety of activities as well as flawed evaluation criteria. This paper aims to help move this research effort forward by introducing a large and varied new dataset called Street Scene, as well as two new evaluation criteria that provide a better estimate of how an algorithm will perform in practice. In addition to the new dataset and evaluation criteria, we present two variations of a novel baseline video anomaly detection algorithm and show they are much more accurate on Street Scene than two state-of-the-art algorithms from the literature.

Includes members:
  Member "real world anomaly detection in surveillance videos":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "centrality graph convolutional networks for skeleton based action recognition")
  Member "object centric auto encoders and dummy anomalies for abnormal event detection in video":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "self trained deep ordinal regression for end to end video anomaly detection")
  Member "detecting abnormal events in video using narrowed normality clusters":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "self trained deep ordinal regression for end to end video anomaly detection")
  Member "abnormal event detection in videos using generative adversarial nets":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "learning a distance function with a siamese network to localize anomalies in videos")
  Member "unmasking the abnormal events in video":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "self trained deep ordinal regression for end to end video anomaly detection")
  Member "joint detection and recounting of abnormal events by learning deep generic knowledge":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "self trained deep ordinal regression for end to end video anomaly detection")
  Member "future frame prediction for anomaly detection a new baseline":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "transformation based adversarial video prediction on large scale data")
  Member "energy based models for video anomaly detection":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "and autoregressive novelty detectors")

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)