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 "a novel method for the absolute pose problem with pairwise constraints"):
  Abstract: Absolute pose estimation is a fundamental problem in computer vision, and it is a typical parameter estimation problem, meaning that efforts to solve it will always suffer from outlier-contaminated data. Conventionally, for a fixed dimensionality d and the number of measurements N, a robust estimation problem cannot be solved faster than O(N^d). Furthermore, it is almost impossible to remove d from the exponent of the runtime of a globally optimal algorithm. However, absolute pose estimation is a geometric parameter estimation problem, and thus has special constraints. In this paper, we consider pairwise constraints and propose a globally optimal algorithm for solving the absolute pose estimation problem. The proposed algorithm has a linear complexity in the number of correspondences at a given outlier ratio. Concretely, we first decouple the rotation and the translation subproblems by utilizing the pairwise constraints, and then we solve the rotation subproblem using the branch-and-bound algorithm. Lastly, we estimate the translation based on the known rotation by using another branch-and-bound algorithm. The advantages of our method are demonstrated via thorough testing on both synthetic and real-world data

Includes members:
  Member "robust fitting in computer vision easy or hard":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "teaser fast and certifiable point cloud registration")
  Member "deterministic consensus maximization with biconvex programming":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "glimps a greedy mixed integer approach for super robust matched subspace detection")
  Member "inloc indoor visual localization with dense matching and view synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "visual camera re localization from rgb and rgb d images using dsac")
  Member "an efficient algebraic solution to the perspective three point problem":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "2 entity ransac for robust visual localization in changing environment")
  Member "efficient global point cloud alignment using bayesian nonparametric mixtures":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "can generalised relative pose estimation solve sparse 3d registration")
  Member "go icp a globally optimal solution to 3d icp point set registration":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "3d point cloud processing and learning for autonomous driving")

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)