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 depth prior for multi view stereo"
  Abstract: It was recently shown that the structure of convolutional neural networks induces a strong prior favoring natural color images, a phenomena referred to as a deep image prior (DIP), which can be an effective regularizer in inverse problems such as image denoising, inpainting etc. In this paper, we investigate a similar idea for depth images, which we call a deep depth prior. Specifically, given a color image and a noisy and incomplete target depth map from the same viewpoint, we optimize a randomly initialized CNN model to reconstruct an RGB-D image where the depth channel gets restored by virtue of using the network structure as a prior. We propose using deep depth priors for refining and inpainting noisy depth maps within a multi-view stereo pipeline. We optimize the network parameters to minimize two losses 1) a RGB-D reconstruction loss based on the noisy depth map and 2) a multi-view photoconsistency-based loss, which is computed using images from a geometrically calibrated camera from nearby viewpoints. Our quantitative and qualitative evaluation shows that our refined depth maps are more accurate and complete, and after fusion, produces dense 3D models of higher quality.

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)