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 "ignor image guided neural object rendering"):
  Abstract: We propose a new learning-based novel view synthesis approach for scanned objects that is trained based on a set of multi-view images. Instead of using texture mapping or hand-designed image-based rendering, we directly train a deep neural network to synthesize a view-dependent image of an object. First, we employ a coverage-based nearest neighbour look-up to retrieve a set of reference frames that are explicitly warped to a given target view using cross-projection. Our network then learns to best composite the warped images. This enables us to generate photo-realistic results, while not having to allocate capacity on `remembering' object appearance. Instead, the multi-view images can be reused. While this works well for diffuse objects, cross-projection does not generalize to view-dependent effects. Therefore, we propose a decomposition network that extracts view-dependent effects and that is trained in a self-supervised manner. After decomposition, the diffuse shading is cross-projected, while the view-dependent layer of the target view is regressed. We show the effectiveness of our approach both qualitatively and quantitatively on real as well as synthetic data.

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 "neural rendering and reenactment of human actor videos":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "neural human video rendering joint learning of dynamic textures and rendering to video translation")
  Member "view extrapolation of human body from a single image":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "monocular neural image based rendering with continuous view control")
  Member "layer structured 3d scene inference via view synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "peelnet textured 3d reconstruction of human body using single view rgb image")
  Member "specular to diffuse translation for multi view reconstruction":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "mini unmanned aerial vehicle based remote sensing techniques applications and prospects")
  Member "a variational u net for conditional appearance and shape generation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "multi channel attention selection gans for guided image to image translation")
  Member "stereo magnification learning view synthesis using multiplane images":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "seeing the world in a bag of chips")
  Member "everybody dance now":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "gan compression efficient architectures for interactive conditional gans")

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)