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: "intra clip aggregation for video person re identification"
  Abstract: Video-based person re-id has drawn much attention in recent years due to its prospective applications in video surveillance. Most existing methods concentrate on how to represent discriminative clip-level features. Moreover, clip-level data augmentation is also important, especially for temporal aggregation task. Inconsistent intra-clip augmentation will collapse inter-frame alignment, thus bringing in additional noise. To tackle the above-motioned problems, we design a novel framework for video-based person re-id, which consists of two main modules: Synchronized Transformation (ST) and Intra-clip Aggregation (ICA). The former module augments intra-clip frames with the same probability and the same operation, while the latter leverages two-level intra-clip encoding to generate more discriminative clip-level features. To confirm the advantage of synchronized transformation, we conduct ablation study with different synchronized transformation scheme. We also perform cross-dataset experiment to better understand the generality of our method. Extensive experiments on three benchmark datasets demonstrate that our framework outperforming the most of recent state-of-the-art methods.

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)