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 "learning 3d human body embedding"):
  Abstract: Although human body shapes vary for different identities with different poses, they can be embedded into a low-dimensional space due to their similarity in structure. Inspired by the recent work on latent representation learning with a deformation-based mesh representation, we propose an autoencoder like network architecture to learn disentangled shape and pose embedding specifically for 3D human body. We also integrate a coarse-to-fine reconstruction pipeline into the disentangling process to improve the reconstruction accuracy. Moreover, we construct a large dataset of human body models with consistent topology for the learning of neural network. Our learned embedding can achieve not only superior reconstruction accuracy but also provide great flexibilities in 3D human body creations via interpolation, bilateral interpolation and latent space sampling, which is confirmed by extensive experiments. The constructed dataset and trained model will be made publicly available.

Includes members:
  Member "disentangled representation learning for 3d face shape":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "3d face modeling from diverse raw scan data")
  Member "generating 3d faces using convolutional mesh autoencoders":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "implicit functions in feature space for 3d shape reconstruction and completion")
  Member "video based reconstruction of 3d people models":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "implicit functions in feature space for 3d shape reconstruction and completion")
  Member "alive caricature from 2d to 3d":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "3d carigan an end to end solution to 3d caricature generation from face photos")
  Member "neural body fitting unifying deep learning and model based human pose and shape estimation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "3d dynamic scene graphs actionable spatial perception with places objects and humans")
  Member "doublefusion real time capture of human performances with inner body shapes from a single depth sensor":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "implicit functions in feature space for 3d shape reconstruction and completion")
  Member "sparse data driven mesh deformation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "rank3dgan semantic mesh generation using relative attributes")
  Member "variational autoencoders for deforming 3d mesh models":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a survey on deep geometry learning from a representation perspective")

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)