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: "scene completenesss aware lidar depth completion for driving scenario"
  Abstract: In this paper we propose Scene Completeness-Aware Depth Completion (SADC) to complete raw lidar scans into dense depth maps with fine whole scene structures. Recent sparse depth completion for lidar only focuses on the lower scenes and produce irregular estimations on the upper because existing datasets such as KITTI do not provide groundtruth for upper areas. These areas are considered less important because they are usually sky or trees and of less scene understanding interest. However, we argue that in several driving scenarios such as large trucks or cars with loads, objects could extend to upper parts of scenes, and thus depth maps with structured upper scene estimation are important for RGBD algorithms. SADC leverages stereo cameras, which have better scene completeness, and lidars, which are more precise, to perform sparse depth completion. To our knowledge, we are the first to focus on scene completeness of sparse depth completion. We validate our SADC on both depth estimate precision and scene-completeness on KITTI. Moreover, SADC only adds small extra computational cost upon base methods of stereo matching and lidar completion in terms of runtime and model size.

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)