human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "the role of rgb d benchmark datasets an overview"
  Abstract: The advent of the Microsoft Kinect three years ago stimulated not only the computer vision community for new algorithms and setups to address well-known problems in the community but also sparked the launch of several new benchmark datasets to which future algorithms can be compared to. This review of the literature and industry developments concludes that the current RGB-D benchmark datasets can be useful to determine the accuracy of a variety of applications of a single or multiple RGB-D sensors.

Connected through hyperedge HE-1 (induced by source paper "rgbd datasets past present and future"):
  with members:
    - "ntu rgb d a large scale dataset for 3d human activity analysis"
    - "a large dataset of object scans"
    - "rgb d based action recognition datasets a survey"
    - "a dataset of naturally occurring whole body background activity to reduce gesture conflicts"
    - "a dataset for improved rgbd based object detection and pose estimation for warehouse pick and place"
    - "scenenet understanding real world indoor scenes with synthetic data"
    - "3d human activity recognition with reconfigurable convolutional neural networks"
    - "cross view action modeling learning and recognition"

Question: Please tell me which class the center node 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)