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: "fast video object segmentation using the global context module"
  Abstract: We developed a real-time, high-quality video object segmentation algorithm for semi-supervised video segmentation. Its performance is on par with the most accurate, time-consuming online-learning model, while its speed is similar to the fastest template-matching method which has sub-optimal accuracy. The core in achieving this is a novel global context module that reliably summarizes and propagates information through the entire video. Compared to previous approaches that only use the first, the last, or a select few frames to guide the segmentation of the current frame, the global context module allows us to use all past frames to guide the processing. Unlike the state-of-the-art space-time memory network that caches a memory at each spatiotemporal position, our global context module is a fixed-size representation that does not use more memory as more frames are processed. It is straightforward in implementation and has lower memory and computational costs than the space-time memory module. Equipped with the global context module, our method achieved top accuracy on DAVIS 2016 and near-state-of-the-art results on DAVIS 2017 at a real-time speed.

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)