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: "real time hand tracking using a sum of anisotropic gaussians model"
  Abstract: Real-time marker-less hand tracking is of increasing importance in human-computer interaction. Robust and accurate tracking of arbitrary hand motion is a challenging problem due to the many degrees of freedom, frequent self-occlusions, fast motions, and uniform skin color. In this paper, we propose a new approach that tracks the full skeleton motion of the hand from multiple RGB cameras in real-time. The main contributions include a new generative tracking method which employs an implicit hand shape representation based on Sum of Anisotropic Gaussians (SAG), and a pose fitting energy that is smooth and analytically differentiable making fast gradient based pose optimization possible. This shape representation, together with a full perspective projection model, enables more accurate hand modeling than a related baseline method from literature. Our method achieves better accuracy than previous methods and runs at 25 fps. We show these improvements both qualitatively and quantitatively on publicly available datasets.

Connected through hyperedge HE-1 (induced by source paper "3d hand pose estimation in the wild via graph refinement under adversarial learning"):
  with members:
    - "3d hand shape and pose estimation from a single rgb image"
    - "3d hand shape and pose from images in the wild"
    - "pushing the envelope for rgb based dense 3d hand pose estimation via neural rendering"
    - "single image 3d hand reconstruction with mesh convolutions"
    - "deepgcns can gcns go as deep as cnns"
    - "disentangling latent hands for image synthesis and pose estimation"
    - "3d human pose estimation in the wild by adversarial learning"
    - "spectral normalization for generative adversarial networks"

Connected through hyperedge HE-2 (induced by source paper "an end to end framework for unconstrained monocular 3d hand pose estimation"):
  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"
    - "single image 3d hand reconstruction with mesh convolutions"
    - "analysis of hand segmentation in the wild"
    - "cross modal deep variational hand pose estimation"
    - "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"

Connected through hyperedge HE-3 (induced by source paper "3d hand shape and pose from images in the wild"):
  with members:
    - "learning pose specific representations by predicting different views"
    - "cross modal deep variational 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"
    - "using a single rgb frame for real time 3d hand pose estimation in the wild"
    - "end to end recovery of human shape and pose"
    - "mofa model based deep convolutional face autoencoder for unsupervised monocular reconstruction"
    - "unpaired image to image translation using cycle consistent adversarial networks"

Connected through hyperedge HE-4 (induced by source paper "convex optimisation for inverse kinematics"):
  with members:
    - "reticam real time human performance capture from monocular video"
    - "convex relaxations for pose graph optimization with outliers"
    - "rotation averaging and strong duality"
    - "ganerated hands for real time 3d hand tracking from monocular rgb"
    - "vnect real time 3d human pose estimation with a single rgb camera"
    - "real time hand tracking under occlusion from an egocentric rgb d sensor"
    - "non iterative rigid 2d 3d point set registration using semidefinite programming"
    - "near optimal joint object matching via convex relaxation"

Connected through hyperedge HE-5 (induced by source paper "hand pose estimation via latent 2 5d heatmap regression"):
  with members:
    - "cross modal deep variational 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"
    - "using a single rgb frame for real time 3d hand pose estimation in the wild"
    - "lifting from the deep convolutional 3d pose estimation from a single image"
    - "compositional human pose regression"
    - "a simple yet effective baseline for 3d human pose estimation"
    - "ganerated hands for real time 3d hand tracking from monocular rgb"

Connected through hyperedge HE-6 (induced by source paper "hands18 methods techniques and applications for hand observation"):
  with members:
    - "task oriented hand motion retargeting for dexterous manipulation imitation"
    - "hand tremor frequency estimation in videos"
    - "hand pose estimation via latent 2 5d heatmap regression"
    - "numerical coordinate regression with convolutional neural networks"
    - "occlusion aware hand pose estimation using hierarchical mixture density network"
    - "unpaired image to image translation using cycle consistent adversarial networks"
    - "cascaded pyramid network for multi person pose estimation"
    - "ganerated hands for real time 3d hand tracking from monocular rgb"

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"
    - "large scale multiview 3d hand pose dataset"
    - "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"

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"
    - "large scale multiview 3d hand pose dataset"
    - "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"

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)