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 "matterport3d learning from rgb d data in indoor environments"):
  Abstract: Access to large, diverse RGB-D datasets is critical for training RGB-D scene understanding algorithms. However, existing datasets still cover only a limited number of views or a restricted scale of spaces. In this paper, we introduce Matterport3D, a large-scale RGB-D dataset containing 10,800 panoramic views from 194,400 RGB-D images of 90 building-scale scenes. Annotations are provided with surface reconstructions, camera poses, and 2D and 3D semantic segmentations. The precise global alignment and comprehensive, diverse panoramic set of views over entire buildings enable a variety of supervised and self-supervised computer vision tasks, including keypoint matching, view overlap prediction, normal prediction from color, semantic segmentation, and region classification.

Includes members:
  Member "deep unsupervised learning through spatial contrasting":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "scattering networks for hybrid representation learning")
  Member "joint 2d 3d semantic data for indoor scene understanding":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "3d point cloud processing and learning for autonomous driving")
  Member "semantic scene completion from a single depth image":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "when deep learning meets data alignment a review on deep registration networks drns")
  Member "lift learned invariant feature transform":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "image matching across wide baselines from paper to practice")
  Member "rgbd datasets past present and future":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "extending maps with semantic and contextual object information for robot navigation a learning based framework using visual and depth cues")
  Member "structured global registration of rgb d scans in indoor environments":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "review deep learning on 3d point clouds")
  Member "learning to navigate the energy landscape":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "hierarchical joint scene coordinate classification and regression for visual localization")
  Member "a large dataset of object scans":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "deep non line of sight reconstruction")

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)