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: "point pair feature based object detection for random bin picking"
  Abstract: Point pair features are a popular representationfor free form 3D object detection and pose estimation. Inthis paper, their performance in an industrial random binpicking context is investigated. A new method to generaterepresentative synthetic datasets is proposed. This allows toinvestigate the influence of a high degree of clutter and thepresence of self similar features, which are typical to ourapplication. We provide an overview of solutions proposedin literature and discuss their strengths and weaknesses. Asimple heuristic method to drastically reduce the computationalcomplexity is introduced, which results in improved robustness, speed and accuracy compared to the naive approach.

Connected through hyperedge HE-1 (induced by source paper "3d object discovery and modeling using single rgb d images containing multiple object instances"):
  with members:
    - "joint 3d reconstruction of a static scene and moving objects"
    - "detecting and grouping identical objects for region proposal and classification"
    - "past present and future of simultaneous localization and mapping toward the robust perception age"

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)