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 "photometric depth super resolution"):
  Abstract: This study explores the use of photometric techniques (shape-from-shading and uncalibrated photometric stereo) for upsampling the low-resolution depth map from an RGB-D sensor to the higher resolution of the companion RGB image. A single-shot variational approach is first put forward, which is effective as long as the target's reflectance is piecewise-constant. It is then shown that this dependency upon a specific reflectance model can be relaxed by focusing on a specific class of objects (e.g., faces), and delegate reflectance estimation to a deep neural network. A multi-shots strategy based on randomly varying lighting conditions is eventually discussed. It requires no training or prior on the reflectance, yet this comes at the price of a dedicated acquisition setup. Both quantitative and qualitative evaluations illustrate the effectiveness of the proposed methods on synthetic and real-world scenarios.

Includes members:
  Member "pixel2mesh generating 3d mesh models from single rgb images":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a survey on deep geometry learning from a representation perspective")
  Member "cnn ps cnn based photometric stereo for general non convex surfaces":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "physics based neural networks for shape from polarization")
  Member "a variational approach to shape from shading under natural illumination":
    also connected through other hyperedges:
      (none)
  Member "learning to predict indoor illumination from a single image":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "seeing the world in a bag of chips")
  Member "led based photometric stereo modeling calibration and numerical solution":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "inferring super resolution depth from a moving light source enhanced rgb d sensor a variational approach")
  Member "variational methods for normal integration":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "normal integration a survey")
  Member "neural face editing with intrinsic image disentangling":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "copy and paste gan face hallucination from shaded thumbnails")
  Member "normal integration a survey":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "inferring super resolution depth from a moving light source enhanced rgb d sensor a variational approach")

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)