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 "monocular 3d object detection in cylindrical images from fisheye cameras"):
  Abstract: Detecting objects in 3D from a monocular camera has been successfully demonstrated using various methods based on convolutional neural networks. These methods have been demonstrated on rectilinear perspective images equivalent to being taken by a pinhole camera, whose geometry is explicitly or implicitly exploited. Such methods fail in images with alternative projections, such as those acquired by fisheye cameras, even when provided with a labeled training set of fisheye images and 3D bounding boxes. In this work, we show how to adapt existing 3D object detection methods to images from fisheye cameras, including in the case that no labeled fisheye data is available for training. We significantly outperform existing art on a benchmark of synthetic data, and we also experiment with an internal dataset of real fisheye images.

Includes members:
  Member "spherical view synthesis for self supervised 360 depth estimation":
    also connected through other hyperedges:
      (none)
  Member "disentangling monocular 3d object detection":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "dsgn deep stereo geometry network for 3d object detection")
  Member "monocular 3d object detection with pseudo lidar point cloud":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "dsgn deep stereo geometry network for 3d object detection")
  Member "nuscenes a multimodal dataset for autonomous driving":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "review deep learning on 3d point clouds")
  Member "unsupervised domain adaptation through self supervision":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multi modal domain adaptation for fine grained action recognition")
  Member "fisheyedistancenet self supervised scale aware distance estimation using monocular fisheye camera for autonomous driving":
    also connected through other hyperedges:
      (none)
  Member "unsupervised learning of depth and ego motion from cylindrical panoramic video":
    also connected through other hyperedges:
      (none)
  Member "reprojection r cnn a fast and accurate object detector for 360 images":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "silhonet fisheye adaptation of a roi based object pose estimation network to monocular fisheye images")

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)