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 "scan2plan efficient floorplan generation from 3d scans of indoor scenes"):
  Abstract: We introduce Scan2Plan, a novel approach for accurate estimation of a floorplan from a 3D scan of the structural elements of indoor environments. The proposed method incorporates a two-stage approach where the initial stage clusters an unordered point cloud representation of the scene into room instances and wall instances using a deep neural network based voting approach. The subsequent stage estimates a closed perimeter, parameterized by a simple polygon, for each individual room by finding the shortest path along the predicted room and wall keypoints. The final floorplan is simply an assembly of all such room perimeters in the global co-ordinate system. The Scan2Plan pipeline produces accurate floorplans for complex layouts, is highly parallelizable and extremely efficient compared to existing methods. The voting module is trained only on synthetic data and evaluated on publicly available Structured3D and BKE datasets to demonstrate excellent qualitative and quantitative results outperforming state-of-the-art techniques.

Includes members:
  Member "floor sp inverse cad for floorplans by sequential room wise shortest path":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "conv mpn convolutional message passing neural network for structured outdoor architecture reconstruction")
  Member "4d spatio temporal convnets minkowski convolutional neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the state of service robots current bottlenecks in object perception and manipulation")
  Member "edge semantic learning strategy for layout estimation in indoor environment":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "indoor layout estimation by 2d lidar and camera fusion")
  Member "flat2layout flat representation for estimating layout of general room types":
    also connected through other hyperedges:
      (none)
  Member "structured3d a large photo realistic dataset for structured 3d modeling":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "fast 3d indoor scene synthesis with discrete and exact layout pattern extraction")
  Member "deep hough voting for 3d object detection in point clouds":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "review deep learning on 3d point clouds")
  Member "deepperimeter indoor boundary estimation from posed monocular sequences":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "indoor layout estimation by 2d lidar and camera fusion")
  Member "layoutnet reconstructing the 3d room layout from a single rgb image":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "the direction aware learnable additive kernels and the adversarial network for deep floor plan recognition")

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)