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: "learning regression and verification networks for long term visual tracking"
  Abstract: Compared with short-term tracking, the long-term tracking task requires determining the tracked object is present or absent, and then estimating the accurate bounding box if present or conducting image-wide re-detection if absent. Until now, few attempts have been done although this task is much closer to designing practical tracking systems. In this work, we propose a novel long-term tracking framework based on deep regression and verification networks. The offline-trained regression model is designed using the object-aware feature fusion and region proposal networks to generate a series of candidates and estimate their similarity scores effectively. The verification network evaluates these candidates to output the optimal one as the tracked object with its classification score, which is online updated to adapt to the appearance variations based on newly reliable observations. The similarity and classification scores are combined to obtain a final confidence value, based on which our tracker can determine the absence of the target accurately and conduct image-wide re-detection to capture the target successfully when it reappears. Extensive experiments show that our tracker achieves the best performance on the VOT2018 long-term challenge and state-of-the-art results on the OxUvA long-term dataset.

Connected through hyperedge HE-1 (induced by source paper "spm tracker series parallel matching for real time visual object tracking"):
  with members:
    - "real time mdnet"
    - "joint representation and truncated inference learning for correlation filter based tracking"
    - "distractor aware siamese networks for visual object tracking"
    - "a twofold siamese network for real time object tracking"
    - "lasot a high quality benchmark for large scale single object tracking"
    - "high speed tracking with multi kernel correlation filters"
    - "unveiling the power of deep tracking"
    - "towards a better match in siamese network based visual object tracker"

Connected through hyperedge HE-2 (induced by source paper "learning to track any object"):
  with members:
    - "got 10k a large high diversity benchmark for generic object tracking in the wild"
    - "tracking without bells and whistles"
    - "feelvos fast end to end embedding learning for video object segmentation"
    - "long term tracking in the wild a benchmark"
    - "fast and accurate online video object segmentation via tracking parts"
    - "distractor aware siamese networks for visual object tracking"
    - "cnn in mrf video object segmentation via inference in a cnn based higher order spatio temporal mrf"
    - "efficient video object segmentation via network modulation"

Connected through hyperedge HE-3 (induced by source paper "skimming perusal tracking a framework for real time and robust long term tracking"):
  with members:
    - "gradnet gradient guided network for visual object tracking"
    - "real time mdnet"
    - "atom accurate tracking by overlap maximization"
    - "long term tracking in the wild a benchmark"
    - "siamese cascaded region proposal networks for real time visual tracking"
    - "distractor aware siamese networks for visual object tracking"
    - "correlation tracking via joint discrimination and reliability learning"
    - "fast online object tracking and segmentation a unifying approach"

Connected through hyperedge HE-4 (induced by source paper "flow guided short term trackers with cascade detection for long term tracking"):
  with members:
    - "region proposal by guided anchoring"
    - "vision meets drones a challenge"
    - "long term tracking in the wild a benchmark"
    - "distractor aware siamese networks for visual object tracking"
    - "yolov3 an incremental improvement"
    - "siamrpn evolution of siamese visual tracking with very deep networks"
    - "now you see me evaluating performance in long term visual tracking"
    - "end to end representation learning for correlation filter based tracking"

Connected through hyperedge HE-5 (induced by source paper "globaltrack a simple and strong baseline for long term tracking"):
  with members:
    - "got 10k a large high diversity benchmark for generic object tracking in the wild"
    - "region proposal by guided anchoring"
    - "learning target oriented dual attention for robust rgb t tracking"
    - "skimming perusal tracking a framework for real time and robust long term tracking"
    - "atom accurate tracking by overlap maximization"
    - "long term tracking in the wild a benchmark"
    - "siamese cascaded region proposal networks for real time visual tracking"
    - "distractor aware siamese networks for visual object tracking"

Connected through hyperedge HE-6 (induced by source paper "exploring 3 r s of long term tracking re detection recovery and reliability"):
  with members:
    - "got 10k a large high diversity benchmark for generic object tracking in the wild"
    - "generalized intersection over union a metric and a loss for bounding box regression"
    - "atom accurate tracking by overlap maximization"
    - "long term tracking in the wild a benchmark"
    - "yolov3 an incremental improvement"
    - "lasot a high quality benchmark for large scale single object tracking"
    - "unveiling the power of deep tracking"
    - "siamrpn evolution of siamese visual tracking with very deep networks"

Connected through hyperedge HE-7 (induced by source paper "cdtb a color and depth visual object tracking dataset and benchmark"):
  with members:
    - "long term tracking in the wild a benchmark"
    - "depth masked discriminative correlation filter"
    - "object tracking by reconstruction with view specific discriminative correlation filters"
    - "now you see me evaluating performance in long term visual tracking"
    - "trackingnet a large scale dataset and benchmark for object tracking in the wild"
    - "fclt a fully correlational long term tracker"
    - "first person hand action benchmark with rgb d videos and 3d hand pose annotations"
    - "learning background aware correlation filters for visual tracking"

Connected through hyperedge HE-8 (induced by source paper "dal a deep depth aware long term tracker"):
  with members:
    - "learning discriminative model prediction for tracking"
    - "got 10k a large high diversity benchmark for generic object tracking in the wild"
    - "atom accurate tracking by overlap maximization"
    - "depth masked discriminative correlation filter"
    - "depth aware cnn for rgb d segmentation"
    - "distractor aware siamese networks for visual object tracking"
    - "object tracking by reconstruction with view specific discriminative correlation filters"
    - "acquisition of localization confidence for accurate object detection"

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)