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 "multi garment net learning to dress 3d people from images"):
  Abstract: We present Multi-Garment Network (MGN), a method to predict body shape and clothing, layered on top of the SMPL model from a few frames (1-8) of a video. Several experiments demonstrate that this representation allows higher level of control when compared to single mesh or voxel representations of shape. Our model allows to predict garment geometry, relate it to the body shape, and transfer it to new body shapes and poses. To train MGN, we leverage a digital wardrobe containing 712 digital garments in correspondence, obtained with a novel method to register a set of clothing templates to a dataset of real 3D scans of people in different clothing and poses. Garments from the digital wardrobe, or predicted by MGN, can be used to dress any body shape in arbitrary poses. We will make publicly available the digital wardrobe, the MGN model, and code to dress SMPL with the garments.

Includes members:
  Member "tex2shape detailed full human body geometry from a single image":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "implicit functions in feature space for 3d shape reconstruction and completion")
  Member "learning to reconstruct people in clothing from a single rgb camera":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "implicit functions in feature space for 3d shape reconstruction and completion")
  Member "pifu pixel aligned implicit function for high resolution clothed human digitization":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "learning to transfer texture from clothing images to 3d humans")
  Member "learning based animation of clothing for virtual try on":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "tailornet predicting clothing in 3d as a function of human pose shape and garment style")
  Member "simulcap single view human performance capture with cloth simulation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "learning to transfer texture from clothing images to 3d humans")
  Member "learning to estimate 3d human pose and shape from a single color image":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "3d dynamic scene graphs actionable spatial perception with places objects and humans")
  Member "instance level human parsing via part grouping network":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "hierarchical human parsing with typed part relation reasoning")
  Member "total capture a 3d deformation model for tracking faces hands and bodies":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "deepcap monocular human performance capture using weak supervision")

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)