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: "robust estimation of similarity transformation for visual object tracking"
  Abstract: Most of existing correlation filter-based tracking approaches only estimate simple axis-aligned bounding boxes, and very few of them is capable of recovering the underlying similarity transformation. To tackle this challenging problem, in this paper, we propose a new correlation filter-based tracker with a novel robust estimation of similarity transformation on the large displacements. In order to efficiently search in such a large 4-DoF space in real-time, we formulate the problem into two 2-DoF sub-problems and apply an efficient Block Coordinates Descent solver to optimize the estimation result. Specifically, we employ an efficient phase correlation scheme to deal with both scale and rotation changes simultaneously in log-polar coordinates. Moreover, a variant of correlation filter is used to predict the translational motion individually. Our experimental results demonstrate that the proposed tracker achieves very promising prediction performance compared with the state-of-the-art visual object tracking methods while still retaining the advantages of high efficiency and simplicity in conventional correlation filter-based tracking methods.

Connected through hyperedge HE-1 (induced by source paper "super deep a surgical perception framework for robotic tissue manipulation using deep learning for feature extraction"):
  with members:
    - "surfelwarp efficient non volumetric single view dynamic reconstruction"
    - "open sourced reinforcement learning environments for surgical robotics"
    - "super a surgical perception framework for endoscopic tissue manipulation with surgical robotics"
    - "mis slam real time large scale dense deformable slam system in minimal invasive surgery based on heterogeneous computing"
    - "augmented reality predictive displays to help mitigate the effects of delayed telesurgery"
    - "pyramid stereo matching network"
    - "simultaneous recognition and pose estimation of instruments in minimally invasive surgery"
    - "fast and reliable autonomous surgical debridement with cable driven robots using a two phase calibration procedure"

Connected through hyperedge HE-2 (induced by source paper "end to end learning of object motion estimation from retinal events for event based object tracking"):
  with members:
    - "event based vision a survey"
    - "atom accurate tracking by overlap maximization"
    - "a unifying contrast maximization framework for event cameras with applications to motion depth and optical flow estimation"
    - "event based moving object detection and tracking"
    - "unsupervised event based learning of optical flow depth and egomotion"
    - "hats histograms of averaged time surfaces for robust event based object classification"
    - "siamrpn evolution of siamese visual tracking with very deep networks"
    - "real time clustering and multi target tracking using event based sensors"

Connected through hyperedge HE-3 (induced by source paper "aggregation signature for small object tracking"):
  with members:
    - "circulant binary convolutional networks enhancing the performance of 1 bit dcnns with circulant back propagation"
    - "state aware anti drift object tracking"
    - "latent constrained correlation filter"
    - "distractor aware siamese networks for visual object tracking"
    - "the world of fast moving objects"
    - "eco efficient convolution operators for tracking"
    - "discriminative scale space tracking"
    - "learning spatially regularized correlation filters for visual tracking"

Connected through hyperedge HE-4 (induced by source paper "super a surgical perception framework for endoscopic tissue manipulation with surgical robotics"):
  with members:
    - "surfelwarp efficient non volumetric single view dynamic reconstruction"
    - "open sourced reinforcement learning environments for surgical robotics"
    - "augmented reality predictive displays to help mitigate the effects of delayed telesurgery"
    - "fast and reliable autonomous surgical debridement with cable driven robots using a two phase calibration procedure"
    - "robot autonomy for surgery"
    - "volumedeform real time volumetric non rigid reconstruction"
    - "real time 3d tracking of articulated tools for robotic surgery"
    - "dense image registration and deformable surface reconstruction in presence of occlusions and minimal texture"

Connected through hyperedge HE-5 (induced by source paper "instant motion tracking and its applications to augmented reality"):
  with members:
    - "planar object tracking in the wild a benchmark"

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)