human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "k means clustering for efficient and robust registration of multi view point sets"):
  Abstract: Efficiency and robustness are the important performance for the registration of multi-view point sets. To address these two issues, this paper casts the multi-view registration into a clustering problem, which can be solved by the extended K-means clustering algorithm. Before the clustering, all the centroids are uniformly sampled from the initially aligned point sets involved in the multi-view registration. Then, two standard K-means steps are utilized to assign all points to one special cluster and update each clustering centroid. Subsequently, the shape comprised by all cluster centroids can be used to sequentially estimate the rigid transformation for each point set. These two standard K-means steps and the step of transformation estimation constitute the extended K-means clustering algorithm, which can achieve the clustering as well as the multi-view registration by iterations. To show its superiority, the proposed approach has tested on some public data sets and compared with the-state-of-art algorithms. Experimental results illustrate its good efficiency and robustness for the registration of multi-view point sets.

Includes members:
  Member "bundlefusion real time globally consistent 3d reconstruction using on the fly surface re integration":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "occuseg occupancy aware 3d instance segmentation")
  Member "outlier robust icp for minimizing fractional rmsd":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "sdrsac semidefinite based randomized approach for robust point cloud registration without correspondences")

Question: Please tell me which class the source paper 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)