human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "deep photometric stereo on a sunny day"
  Abstract: Photometric Stereo in outdoor illumination remains a challenging, ill-posed problem. Indeed, it has been shown that the scene structure cannot be recovered unambiguously from the photometric cues alone when it is lit by the sun over the course of a single day. In this paper, we present a CNN-based technique for photometric stereo on a single sunny day. We solve the ambiguity issue by combining photometric cues with prior knowledge on material properties, local surface geometry and the natural variations in outdoor lighting. To train the CNN, we create a dataset of realistic synthetic renders with both diffuse and specular materials. Given eight outdoor images taken during a single sunny day, our method robustly estimates the scene surface normals. Our approach does not require precise geolocation to work and significantly outperforms several state-of-the-art methods on images with real lighting. This shows that our CNN can combine efficiently learned priors and photometric cues available during a single sunny day.

Connected through hyperedge HE-1 (induced by source paper "variational uncalibrated photometric stereo under general lighting"):
  with members:
    - "photometric depth super resolution"
    - "depth super resolution meets uncalibrated photometric stereo"
    - "normal integration a survey"

Question: Please tell me which class the center node 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)