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 "estimation of camera locations in highly corrupted scenarios all about that base no shape trouble"):
  Abstract: We propose a strategy for improving camera location estimation in structure from motion. Our setting assumes highly corrupted pairwise directions (i.e., normalized relative location vectors), so there is a clear room for improving current state-of-the-art solutions for this problem. Our strategy identifies severely corrupted pairwise directions by using a geometric consistency condition. It then selects a cleaner set of pairwise directions as a preprocessing step for common solvers. We theoretically guarantee the successful performance of a basic version of our strategy under a synthetic corruption model. Numerical results on artificial and real data demonstrate the significant improvement obtained by our strategy.

Includes members:
  Member "exact camera location recovery by least unsquared deviations":
    also connected through other hyperedges:
      (none)
  Member "a new rank constraint on multi view fundamental matrices and its application to camera location recovery":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "averaging essential and fundamental matrices in collinear camera settings")
  Member "a survey of structure from motion":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "robust attentional aggregation of deep feature sets for multi view 3d reconstruction")
  Member "shapefit and shapekick for robust scalable structure from motion":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "algebraic characterization of essential matrices and their averaging in multiview settings")
  Member "shapefit exact location recovery from corrupted pairwise directions":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "exact camera location recovery by least unsquared deviations")
  Member "robust camera location estimation by convex programming":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "learning transformation synchronization")
  Member "stable camera motion estimation using convex programming":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "algebraic representations for volumetric frame fields")

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)