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: "reconstructing articulated rigged models from rgb d videos"
  Abstract: Although commercial and open-source software exist to reconstruct a static object from a sequence recorded with an RGB-D sensor, there is a lack of tools that build rigged models of articulated objects that deform realistically and can be used for tracking or animation. In this work, we fill this gap and propose a method that creates a fully rigged model of an articulated object from depth data of a single sensor. To this end, we combine deformable mesh tracking, motion segmentation based on spectral clustering and skeletonization based on mean curvature flow. The fully rigged model then consists of a watertight mesh, embedded skeleton, and skinning weights.

Connected through hyperedge HE-1 (induced by source paper "deep part induction from articulated object pairs"):
  with members:
    - "splatnet sparse lattice networks for point cloud processing"
    - "motion based object segmentation based on dense rgb d scene flow"
    - "escape from cells deep kd networks for the recognition of 3d point cloud models"
    - "lifting from the deep convolutional 3d pose estimation from a single image"
    - "o cnn octree based convolutional neural networks for 3d shape analysis"
    - "pointnet deep hierarchical feature learning on point sets in a metric space"
    - "vnect real time 3d human pose estimation with a single rgb camera"
    - "multiframe scene flow with piecewise rigid motion"

Connected through hyperedge HE-2 (induced by source paper "em fusion dynamic object level slam with probabilistic data association"):
  with members:
    - "fusion volumetric object level slam"
    - "mid fusion octree based object level multi instance dynamic slam"
    - "co fusion real time segmentation tracking and fusion of multiple objects"
    - "mask r cnn"
    - "probabilistic articulated real time tracking for robot manipulation"

Connected through hyperedge HE-3 (induced by source paper "articulatedfusion real time reconstruction of motion geometry and segmentation using a single depth camera"):
  with members:
    - "doublefusion real time capture of human performances with inner body shapes from a single depth sensor"
    - "volumedeform real time volumetric non rigid reconstruction"
    - "surface approximation via asymptotic optimal geometric partition"

Connected through hyperedge HE-4 (induced by source paper "co fusion real time segmentation tracking and fusion of multiple objects"):
  with members:
    - "virtual worlds as proxy for multi object tracking analysis"
    - "learning to refine object segments"
    - "gslicr slic superpixels at over 250hz"
    - "efficient inference in fully connected crfs with gaussian edge potentials"

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)