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: "characterization of a rs lidar for 3d perception"
  Abstract: High precision 3D LiDARs are still expensive and hard to acquire. This paper presents the characteristics of RS-LiDAR, a model of low-cost LiDAR with sufficient supplies, in comparison with VLP-16. The paper also provides a set of evaluations to analyze the characterizations and performances of LiDARs sensors. This work analyzes multiple properties, such as drift effects, distance effects, color effects and sensor orientation effects, in the context of 3D perception. By comparing with Velodyne LiDAR, we found RS-LiDAR as a cheaper and acquirable substitute of VLP-16 with similar efficiency.

Connected through hyperedge HE-1 (induced by source paper "a new approach to 3d icp covariance estimation"):
  with members:
    - "cello 3d estimating the covariance of icp in the real world"
    - "imls slam scan to model matching based on 3d data"
    - "lidar measurement bias estimation via return waveform modelling in a context of 3d mapping"
    - "on the covariance of icp based scan matching techniques"
    - "the invariant extended kalman filter as a stable observer"

Connected through hyperedge HE-2 (induced by source paper "person in wifi fine grained person perception using wifi"):
  with members:
    - "joint activity recognition and indoor localization with wifi fingerprints"
    - "efficient continuous time slam for 3d lidar based online mapping"
    - "csi net unified human body characterization and action recognition"
    - "total capture a 3d deformation model for tracking faces hands and bodies"
    - "simple baselines for human pose estimation and tracking"
    - "efficient online multi person 2d pose tracking with recurrent spatio temporal affinity fields"
    - "combining lidar space clustering and convolutional neural networks for pedestrian detection"
    - "towards accurate multi person pose estimation in the wild"

Connected through hyperedge HE-3 (induced by source paper "focal loss in 3d object detection"):
  with members:
    - "joint 3d proposal generation and object detection from view aggregation"
    - "voxelnet end to end learning for point cloud based 3d object detection"
    - "focal loss for dense object detection"
    - "frustum pointnets for 3d object detection from rgb d data"
    - "mask r cnn"
    - "ssd single shot multibox detector"
    - "3d fully convolutional network for vehicle detection in point cloud"
    - "feature pyramid networks for object detection"

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.RO(Robotics)