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 "neural point based graphics"):
  Abstract: We present a new point-based approach for modeling complex scenes. The approach uses a raw point cloud as the geometric representation of a scene, and augments each point with a learnable neural descriptor that encodes local geometry and appearance. A deep rendering network is learned in parallel with the descriptors, so that new views of the scene can be obtained by passing the rasterizations of a point cloud from new viewpoints through this network. The input rasterizations use the learned descriptors as point pseudo-colors. We show that the proposed approach can be used for modeling complex scenes and obtaining their photorealistic views, while avoiding explicit surface estimation and meshing. In particular, compelling results are obtained for scene scanned using hand-held commodity RGB-D sensors as well as standard RGB cameras even in the presence of objects that are challenging for standard mesh-based modeling.

Includes members:
  Member "deferred neural rendering image synthesis using neural textures":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "deepfakes and beyond a survey of face manipulation and fake detection")
  Member "lookingood enhancing performance capture with real time neural re rendering":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "neural voxel renderer learning an accurate and controllable rendering tool")
  Member "free form image inpainting with gated convolution":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "cooperative semantic segmentation and image restoration in adverse environmental conditions")
  Member "ignor image guided neural object rendering":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "3d ken burns effect from a single image")
  Member "deep surface light fields":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "seeing the world in a bag of chips")
  Member "deep shading convolutional neural networks for screen space shading":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "deltra deep light transport for projector camera systems")
  Member "progressive growing of gans for improved quality stability and variation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "generative adversarial networks in computer vision a survey and taxonomy")
  Member "high resolution image synthesis and semantic manipulation with conditional gans":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "generative adversarial networks in computer vision a survey and taxonomy")

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)