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: "non line of sight tracking of people at long range"
  Abstract: A remote-sensing system that can determine the position of hidden objects has applications in many critical real-life scenarios, such as search and rescue missions and safe autonomous driving. Previous work has shown the ability to range and image objects hidden from the direct line of sight, employing advanced optical imaging technologies aimed at small objects at short range. In this work we demonstrate a long-range tracking system based on single laser illumination and single-pixel single-photon detection. This enables us to track one or more people hidden from view at a stand-off distance of over 50~m. These results pave the way towards next generation LiDAR systems that will reconstruct not only the direct-view scene but also the main elements hidden behind walls or corners.

Connected through hyperedge HE-1 (induced by source paper "seeing around street corners non line of sight detection and tracking in the wild using doppler radar"):
  with members:
    - "pointpillars fast encoders for object detection from point clouds"
    - "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"
    - "neural network identification of people hidden from view with a single pixel single photon detector"
    - "optically lightweight tracking of objects around a corner"
    - "multi view 3d object detection network for autonomous driving"
    - "you only look once unified real time object detection"

Connected through hyperedge HE-2 (induced by source paper "steady state non line of sight imaging"):
  with members:
    - "non line of sight imaging with partial occluders and surface normals"
    - "robust non line of sight imaging with single photon detectors"
    - "neural network identification of people hidden from view with a single pixel single photon detector"
    - "unsupervised monocular depth estimation with left right consistency"
    - "synthesizing training images for boosting human 3d pose estimation"
    - "optically lightweight tracking of objects around a corner"
    - "u net convolutional networks for biomedical image segmentation"
    - "segnet a deep convolutional encoder decoder architecture for image segmentation"

Connected through hyperedge HE-3 (induced by source paper "neural network identification of people hidden from view with a single pixel single photon detector"):
  with members:
    - "lensless computational imaging through deep learning"
    - "exploit imaging through opaque wall via deep learning"
    - "optically lightweight tracking of objects around a corner"
    - "deep learning in neural networks"

Connected through hyperedge HE-4 (induced by source paper "non line of sight imaging with partial occluders and surface normals"):
  with members:
    - "fast back projection for non line of sight reconstruction"
    - "optically lightweight tracking of objects around a corner"

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)