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: "large scale multiview 3d hand pose dataset"
  Abstract: Accurate hand pose estimation at joint level has several uses on human-robot interaction, user interfacing and virtual reality applications. Yet, it currently is not a solved problem. The novel deep learning techniques could make a great improvement on this matter but they need a huge amount of annotated data. The hand pose datasets released so far present some issues that make them impossible to use on deep learning methods such as the few number of samples, high-level abstraction annotations or samples consisting in depth maps. In this work, we introduce a multiview hand pose dataset in which we provide color images of hands and different kind of annotations for each, i.e the bounding box and the 2D and 3D location on the joints in the hand. Besides, we introduce a simple yet accurate deep learning architecture for real-time robust 2D hand pose estimation.

Connected through hyperedge HE-1 (induced by source paper "rotation invariant mixed graphical model network for 2d hand pose estimation"):
  with members:
    - "adaptive graphical model network for 2d handpose estimation"
    - "3d hand shape and pose estimation from a single rgb image"
    - "geometric pose affordance 3d human pose with scene constraints"
    - "3d hand shape and pose from images in the wild"
    - "deep high resolution representation learning for human pose estimation"
    - "openpose realtime multi person 2d pose estimation using part affinity fields"
    - "multi scale structure aware network for human pose estimation"
    - "augmented skeleton space transfer for depth based hand pose estimation"

Connected through hyperedge HE-2 (induced by source paper "attention a lightweight 2d hand pose estimation approach"):
  with members:
    - "real time facial surface geometry from monocular video on mobile gpus"
    - "making convolutional networks shift invariant again"
    - "freihand a dataset for markerless capture of hand pose and shape from single rgb images"
    - "an empirical study of spatial attention mechanisms in deep networks"
    - "3d hand shape and pose from images in the wild"
    - "attention augmented convolutional networks"
    - "mish a self regularized non monotonic neural activation function"
    - "openpose realtime multi person 2d pose estimation using part affinity fields"

Connected through hyperedge HE-3 (induced by source paper "end to end hand mesh recovery from a monocular rgb image"):
  with members:
    - "3d hand shape and pose estimation from a single rgb image"
    - "3d hand shape and pose from images in the wild"
    - "face alignment in full pose range a 3d total solution"
    - "learning to estimate 3d human pose and shape from a single color image"
    - "bodynet volumetric inference of 3d human body shapes"
    - "total capture a 3d deformation model for tracking faces hands and bodies"
    - "augmented skeleton space transfer for depth based hand pose estimation"
    - "neural body fitting unifying deep learning and model based human pose and shape estimation"

Connected through hyperedge HE-4 (induced by source paper "freihand a dataset for markerless capture of hand pose and shape from single rgb images"):
  with members:
    - "3d hand shape and pose estimation from a single rgb image"
    - "learning joint reconstruction of hands and manipulated objects"
    - "3d hand shape and pose from images in the wild"
    - "total capture a 3d deformation model for tracking faces hands and bodies"
    - "uncertainty estimates and multi hypotheses networks for optical flow"
    - "hand pose estimation via latent 2 5d heatmap regression"
    - "learning to estimate 3d hand pose from single rgb images"
    - "learning a multi view stereo machine"

Connected through hyperedge HE-5 (induced by source paper "adaptive graphical model network for 2d handpose estimation"):
  with members:
    - "geometric pose affordance 3d human pose with scene constraints"
    - "openpose realtime multi person 2d pose estimation using part affinity fields"
    - "augmented skeleton space transfer for depth based hand pose estimation"
    - "thin slicing network a deep structured model for pose estimation in videos"
    - "learning to estimate 3d hand pose from single rgb images"
    - "using a single rgb frame for real time 3d hand pose estimation in the wild"
    - "towards accurate multi person pose estimation in the wild"
    - "dense 3d regression for hand pose estimation"

Connected through hyperedge HE-6 (induced by source paper "adaptive wasserstein hourglass for weakly supervised hand pose estimation from monocular rgb"):
  with members:
    - "3d hand shape and pose estimation from a single rgb image"
    - "3d hand shape and pose from images in the wild"
    - "domain transfer for 3d pose estimation from color images without manual annotations"
    - "3d human pose estimation in the wild by adversarial learning"
    - "tadam task dependent adaptive metric for improved few shot learning"
    - "hand pose estimation via latent 2 5d heatmap regression"
    - "cross modal deep variational hand pose estimation"
    - "learning to estimate 3d hand pose from single rgb images"

Connected through hyperedge HE-7 (induced by source paper "ganerated hands for real time 3d hand tracking from monocular rgb"):
  with members:
    - "crossing nets combining gans and vaes with a shared latent space for hand pose estimation"
    - "learning to estimate 3d hand pose from single rgb images"
    - "back to rgb 3d tracking of hands and hand object interactions based on short baseline stereo"
    - "synthetic to real adaptation with generative correlation alignment networks"
    - "adversarial discriminative domain adaptation"
    - "unpaired image to image translation using cycle consistent adversarial networks"
    - "learning from synthetic humans"
    - "learning human pose models from synthesized data for robust rgb d action recognition"

Connected through hyperedge HE-8 (induced by source paper "using a single rgb frame for real time 3d hand pose estimation in the wild"):
  with members:
    - "pose guided structured region ensemble network for cascaded hand pose estimation"
    - "learning to estimate 3d hand pose from single rgb images"
    - "back to rgb 3d tracking of hands and hand object interactions based on short baseline stereo"
    - "deepprior improving fast and accurate 3d hand pose estimation"
    - "compositional human pose regression"
    - "towards good practices for deep 3d hand pose estimation"
    - "dynamics based 3d skeletal hand tracking"
    - "vnect real time 3d human pose estimation with a single rgb camera"

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.HC(Human-Computer Interaction)