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: "3d carigan an end to end solution to 3d caricature generation from face photos"
  Abstract: Caricature is a kind of artistic style of human faces that attracts considerable research in computer vision. So far all existing 3D caricature generation methods require some information related to caricature as input, e.g., a caricature sketch or 2D caricature. However, this kind of input is difficult to provide by non-professional users. In this paper, we propose an end-to-end deep neural network model to generate high-quality 3D caricature with a simple face photo as input. The most challenging issue in our system is that the source domain of face photos (characterized by 2D normal faces) is significantly different from the target domain of 3D caricatures (characterized by 3D exaggerated face shapes and texture). To address this challenge, we (1) build a large dataset of 6,100 3D caricature meshes and use it to establish a PCA model in the 3D caricature shape space and (2) detect landmarks in the input face photo and use them to set up correspondence between 2D caricature and 3D caricature shape. Our system can automatically generate high-quality 3D caricatures. In many situations, users want to control the output by a simple and intuitive way, so we further introduce a simple-to-use interactive control with three horizontal and one vertical lines. Experiments and user studies show that our system is easy to use and can generate high-quality 3D caricatures.

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)