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: "layoutnet reconstructing the 3d room layout from a single rgb image"
  Abstract: We propose an algorithm to predict room layout from a single image that generalizes across panoramas and perspective images, cuboid layouts and more general layouts (e.g. L-shape room). Our method operates directly on the panoramic image, rather than decomposing into perspective images as do recent works. Our network architecture is similar to that of RoomNet, but we show improvements due to aligning the image based on vanishing points, predicting multiple layout elements (corners, boundaries, size and translation), and fitting a constrained Manhattan layout to the resulting predictions. Our method compares well in speed and accuracy to other existing work on panoramas, achieves among the best accuracy for perspective images, and can handle both cuboid-shaped and more general Manhattan layouts.

Connected through hyperedge HE-1 (induced by source paper "scan2plan efficient floorplan generation from 3d scans of indoor scenes"):
  with members:
    - "floor sp inverse cad for floorplans by sequential room wise shortest path"
    - "4d spatio temporal convnets minkowski convolutional neural networks"
    - "edge semantic learning strategy for layout estimation in indoor environment"
    - "flat2layout flat representation for estimating layout of general room types"
    - "structured3d a large photo realistic dataset for structured 3d modeling"
    - "deep hough voting for 3d object detection in point clouds"
    - "deepperimeter indoor boundary estimation from posed monocular sequences"
    - "deep clustering for unsupervised learning of visual features"

Connected through hyperedge HE-2 (induced by source paper "the direction aware learnable additive kernels and the adversarial network for deep floor plan recognition"):
  with members:
    - "deep floor plan recognition using a multi task network with room boundary guided attention"
    - "horizonnet learning room layout with 1d representation and pano stretch data augmentation"
    - "acnet strengthening the kernel skeletons for powerful cnn via asymmetric convolution blocks"
    - "dula net a dual projection network for estimating room layouts from a single rgb panorama"
    - "encoder decoder with atrous separable convolution for semantic image segmentation"
    - "cycada cycle consistent adversarial domain adaptation"
    - "a fast rcnn hard positive generation via adversary for object detection"
    - "generative face completion"

Connected through hyperedge HE-3 (induced by source paper "indoor layout estimation by 2d lidar and camera fusion"):
  with members:
    - "edge semantic learning strategy for layout estimation in indoor environment"
    - "deepperimeter indoor boundary estimation from posed monocular sequences"
    - "floornet a unified framework for floorplan reconstruction from 3d scans"

Connected through hyperedge HE-4 (induced by source paper "cross view semantic segmentation for sensing surroundings"):
  with members:
    - "nuscenes a multimodal dataset for autonomous driving"
    - "high resolution representations for labeling pixels and regions"
    - "learning exploration policies for navigation"
    - "learning to adapt structured output space for semantic segmentation"
    - "cross view image synthesis using conditional gans"
    - "dcan dual channel wise alignment networks for unsupervised scene adaptation"
    - "visual memory for robust path following"
    - "gibson env real world perception for embodied agents"

Connected through hyperedge HE-5 (induced by source paper "object driven multi layer scene decomposition from a single image"):
  with members:
    - "peeking behind objects layered depth prediction from a single image"
    - "deep depth completion of a single rgb d image"
    - "planercnn 3d plane detection and reconstruction from a single image"
    - "layer structured 3d scene inference via view synthesis"
    - "stereo magnification learning view synthesis using multiplane images"
    - "adversarial semantic scene completion from a single depth image"
    - "segan segmenting and generating the invisible"
    - "multi scale continuous crfs as sequential deep networks for monocular depth estimation"

Connected through hyperedge HE-6 (induced by source paper "clouds of oriented gradients for 3d detection of objects surfaces and indoor scene layouts"):
  with members:
    - "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"
    - "pointnet deep hierarchical feature learning on point sets in a metric space"
    - "roomnet end to end room layout estimation"
    - "semantic scene completion from a single depth image"
    - "3d object proposals using stereo imagery for accurate object class detection"
    - "3d bounding box estimation using deep learning and geometry"

Connected through hyperedge HE-7 (induced by source paper "zero shot task transfer"):
  with members:
    - "latent ransac"
    - "bayesian model agnostic meta learning"
    - "taskonomy disentangling task transfer learning"
    - "adversarial data programming using gans to relax the bottleneck of curated labeled data"
    - "domain adaptation for visual applications a comprehensive survey"
    - "maximum classifier discrepancy for unsupervised domain adaptation"
    - "zero shot task generalization with multi task deep reinforcement learning"
    - "roomnet end to end room layout estimation"

Connected through hyperedge HE-8 (induced by source paper "structured3d a large photo realistic dataset for structured 3d modeling"):
  with members:
    - "floor sp inverse cad for floorplans by sequential room wise shortest path"
    - "3d manhattan room layout reconstruction from a single 360 image"
    - "single image piece wise planar 3d reconstruction via associative embedding"
    - "horizonnet learning room layout with 1d representation and pano stretch data augmentation"
    - "learning to reconstruct 3d manhattan wireframes from a single image"
    - "learning to adapt structured output space for semantic segmentation"
    - "dula net a dual projection network for estimating room layouts from a single rgb panorama"
    - "planenet piece wise planar reconstruction from a single rgb image"

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)