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: "rotation averaging and strong duality"
  Abstract: In this paper we explore the role of duality principles within the problem of rotation averaging, a fundamental task in a wide range of computer vision applications. In its conventional form, rotation averaging is stated as a minimization over multiple rotation constraints. As these constraints are non-convex, this problem is generally considered challenging to solve globally. We show how to circumvent this difficulty through the use of Lagrangian duality. While such an approach is well-known it is normally not guaranteed to provide a tight relaxation. Based on spectral graph theory, we analytically prove that in many cases there is no duality gap unless the noise levels are severe. This allows us to obtain certifiably global solutions to a class of important non-convex problems in polynomial time. #R##N#We also propose an efficient, scalable algorithm that out-performs general purpose numerical solvers and is able to handle the large problem instances commonly occurring in structure from motion settings. The potential of this proposed method is demonstrated on a number of different problems, consisting of both synthetic and real-world data.

Connected through hyperedge HE-1 (induced by source paper "on the distribution of minima in intrinsic metric rotation averaging"):
  with members:
    - "cramer rao bounds for synchronization of rotations"
    - "exact and stable recovery of rotations for robust synchronization"
    - "a tutorial on spectral clustering"

Connected through hyperedge HE-2 (induced by source paper "convex optimisation for inverse kinematics"):
  with members:
    - "reticam real time human performance capture from monocular video"
    - "convex relaxations for pose graph optimization with outliers"
    - "ganerated hands for real time 3d hand tracking from monocular rgb"
    - "vnect real time 3d human pose estimation with a single rgb camera"
    - "real time hand tracking under occlusion from an egocentric rgb d sensor"
    - "non iterative rigid 2d 3d point set registration using semidefinite programming"
    - "near optimal joint object matching via convex relaxation"
    - "real time hand tracking using a sum of anisotropic gaussians model"

Connected through hyperedge HE-3 (induced by source paper "graduated non convexity for robust spatial perception from non minimal solvers to global outlier rejection"):
  with members:
    - "a polynomial time solution for robust registration with extreme outlier rates"
    - "cvxpnpl a unified convex solution to the absolute pose estimation problem from point and line correspondences"
    - "convex relaxations for pose graph optimization with outliers"
    - "accelerated inference in markov random fields via smooth riemannian optimization"
    - "modeling perceptual aliasing in slam via discrete continuous graphical models"
    - "guaranteed outlier removal for point cloud registration with correspondences"
    - "robust fitting in computer vision easy or hard"
    - "sparse representation for 3d shape estimation a convex relaxation approach"

Connected through hyperedge HE-4 (induced by source paper "certifiably globally optimal extrinsic calibration from per sensor egomotion"):
  with members:
    - "self calibration of mobile manipulator kinematic and sensor extrinsic parameters through contact based interaction"
    - "entropy based sim 3 calibration of 2d lidars to egomotion sensors"
    - "a certifiably correct algorithm for synchronization over the special euclidean group"
    - "efficient global point cloud alignment using bayesian nonparametric mixtures"
    - "lagrangian duality in 3d slam verification techniques and optimal solutions"
    - "hand eye and robot world calibration by global polynomial optimization"

Connected through hyperedge HE-5 (induced by source paper "algebraic characterization of essential matrices and their averaging in multiview settings"):
  with members:
    - "resultant based incremental recovery of camera pose from pairwise matches"
    - "gpsfm global projective sfm using algebraic constraints on multi view fundamental matrices"
    - "a new rank constraint on multi view fundamental matrices and its application to camera location recovery"
    - "shapefit and shapekick for robust scalable structure from motion"
    - "linear global translation estimation with feature tracks"
    - "robust camera location estimation by convex programming"

Connected through hyperedge HE-6 (induced by source paper "neurora neural robust rotation averaging"):
  with members:
    - "pointnetlk robust efficient point cloud registration using pointnet"
    - "taking a deeper look at the inverse compositional algorithm"
    - "neural message passing for quantum chemistry"
    - "learning combinatorial optimization algorithms over graphs"
    - "posenet a convolutional network for real time 6 dof camera relocalization"

Connected through hyperedge HE-7 (induced by source paper "graph based parallel large scale structure from motion"):
  with members:
    - "baseline desensitizing in translation averaging"
    - "parallel structure from motion from local increment to global averaging"
    - "large scale sfm with the distributed camera model"
    - "hierarchical structure and motion recovery from uncalibrated images"
    - "robust camera location estimation by convex programming"

Connected through hyperedge HE-8 (induced by source paper "event based star tracking via multiresolution progressive hough transforms"):
  with members:
    - "empirical analysis of common subgraph isomorphism approaches to the lost in space star identification problem"
    - "a unifying contrast maximization framework for event cameras with applications to motion depth and optical flow estimation"
    - "star tracking using an event camera"
    - "robust fitting in computer vision easy or hard"
    - "real time panoramic tracking for event cameras"

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)