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: "pupil an open source platform for pervasive eye tracking and mobile gaze based interaction"
  Abstract: Commercial head-mounted eye trackers provide useful features to customers in industry and research but are expensive and rely on closed source hardware and software. This limits the application areas and use of mobile eye tracking to expert users and inhibits user-driven development, customisation, and extension. In this paper we present Pupil -- an accessible, affordable, and extensible open source platform for mobile eye tracking and gaze-based interaction. Pupil comprises 1) a light-weight headset with high-resolution cameras, 2) an open source software framework for mobile eye tracking, as well as 3) a graphical user interface (GUI) to playback and visualize video and gaze data. Pupil features high-resolution scene and eye cameras for monocular and binocular gaze estimation. The software and GUI are platform-independent and include state-of-the-art algorithms for real-time pupil detection and tracking, calibration, and accurate gaze estimation. Results of a performance evaluation show that Pupil can provide an average gaze estimation accuracy of 0.6 degree of visual angle (0.08 degree precision) with a latency of the processing pipeline of only 0.045 seconds.

Connected through hyperedge HE-1 (induced by source paper "differential privacy for eye tracking with temporal correlations"):
  with members:
    - "differential privacy for eye tracking data"
    - "secure and reliable key agreement with physical unclonable functions"
    - "privacy aware eye tracking using differential privacy"
    - "collecting telemetry data privately"

Connected through hyperedge HE-2 (induced by source paper "are you really looking at me a feature extraction framework for estimating interpersonal eye gaze from conventional video"):
  with members:
    - "a review and analysis of eye gaze estimation systems algorithms and performance evaluation methods in consumer platforms"
    - "real time eye gaze direction classification using convolutional neural network"
    - "appearance based gaze estimation in the wild"

Connected through hyperedge HE-3 (induced by source paper "the security utility trade off for iris authentication and eye animation for social virtual avatars"):
  with members:
    - "differential privacy for eye tracking data"
    - "deep appearance models for face rendering"
    - "privacy aware eye tracking using differential privacy"

Connected through hyperedge HE-4 (induced by source paper "action anticipation for collaborative environments the impact of contextual information and uncertainty based prediction"):
  with members:
    - "delving into 3d action anticipation from streaming videos"
    - "action anticipation with rbf kernelized feature mapping rnn"
    - "early action prediction with generative adversarial networks"
    - "anticipation and next action forecasting in video an end to end model with memory"
    - "openpose realtime multi person 2d pose estimation using part affinity fields"
    - "human action recognition and prediction a survey"
    - "action anticipation by predicting future dynamic images"
    - "anticipation in human robot cooperation a recurrent neural network approach for multiple action sequences prediction"

Connected through hyperedge HE-5 (induced by source paper "image based eye gaze tracking and its applications"):
  with members:
    - "escaf pupil centre localization algorithm with candidate filtering"
    - "recognition of activities from eye gaze and egocentric video"
    - "labelled pupils in the wild a dataset for studying pupil detection in unconstrained environments"
    - "a framework for fast face and eye detection"
    - "else ellipse selection for robust pupil detection in real world environments"
    - "a drowsiness detection scheme based on fusion of voice and vision cues"
    - "appearance based gaze estimation in the wild"
    - "design and implementation of real time algorithms for eye tracking and perclos measurement for on board estimation of alertness of drivers"

Connected through hyperedge HE-6 (induced by source paper "deep neural network and data augmentation methodology for off axis iris segmentation in wearable headsets"):
  with members:
    - "embedding structured contour and location prior in siamesed fully convolutional networks for road detection"
    - "segdensenet iris segmentation for pre and post cataract surgery"
    - "encoder decoder with atrous separable convolution for semantic image segmentation"
    - "smart augmentation learning an optimal data augmentation strategy"
    - "a survey of augmented reality navigation"
    - "deep convolutional neural networks and data augmentation for environmental sound classification"
    - "deeplab semantic image segmentation with deep convolutional nets atrous convolution and fully connected crfs"
    - "gesture based continuous authentication for wearable devices the google glass case"

Connected through hyperedge HE-7 (induced by source paper "gaze in wild a dataset for studying eye and head coordination in everyday activities"):
  with members:
    - "generalised dice overlap as a deep learning loss function for highly unbalanced segmentations"
    - "end to end eye movement detection using convolutional neural networks"
    - "bayesian identification of fixations saccades and smooth pursuits"
    - "adam a method for stochastic optimization"
    - "empirical evaluation of gated recurrent neural networks on sequence modeling"

Connected through hyperedge HE-8 (induced by source paper "how far are we from quantifying visual attention in mobile hci"):
  with members:
    - "forecasting user attention during everyday mobile interactions using device integrated and wearable sensors"
    - "mpiigaze real world dataset and deep appearance based gaze estimation"
    - "eye tracking for everyone"
    - "it s written all over your face full face appearance based gaze estimation"
    - "appearance based gaze estimation in the wild"

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)