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: "toward storytelling from visual lifelogging an overview"
  Abstract: Visual lifelogging consists of acquiring images that capture the daily experiences of the user by wearing a camera over a long period of time. The pictures taken offer considerable potential for knowledge mining concerning how people live their lives; hence, they open up new opportunities for many potential applications in fields including healthcare, security, leisure, and the quantified self. However, automatically building a story from a huge collection of unstructured egocentric data presents major challenges. This paper provides a thorough review of advances made so far in egocentric data analysis and, in view of the current state of the art, indicates new lines of research to move us toward storytelling from visual lifelogging.

Connected through hyperedge HE-1 (induced by source paper "analysis of the hands in egocentric vision a survey"):
  with members:
    - "an effective and efficient method for detecting hands in egocentric videos for rehabilitation applications"
    - "recurrent u net for resource constrained segmentation"
    - "h o unified egocentric recognition of 3d hand object poses and interactions"
    - "domain specific priors and meta learning for low shot first person action recognition"
    - "egocentric hand track and object based human action recognition"
    - "egocentric video a new tool for capturing hand use of individuals with spinal cord injury at home"
    - "scaling egocentric vision the epic kitchens dataset"
    - "analysis of hand segmentation in the wild"

Connected through hyperedge HE-2 (induced by source paper "learning event representations in image sequences by dynamic graph embedding"):
  with members:
    - "predicting visual context for unsupervised event segmentation in continuous photo streams"
    - "egocentric video description based on temporally linked sequences"
    - "r clustering for egocentric video segmentation"
    - "harp hierarchical representation learning for networks"
    - "representation learning on graphs methods and applications"
    - "sr clustering semantic regularized clustering for egocentric photo streams segmentation"
    - "geometric deep learning going beyond euclidean data"
    - "node2vec scalable feature learning for networks"

Connected through hyperedge HE-3 (induced by source paper "social relation recognition in egocentric photostreams"):
  with members:
    - "person recognition in personal photo collections"
    - "batch based activity recognition from egocentric photo streams revisited"
    - "a domain based approach to social relation recognition"
    - "sr clustering semantic regularized clustering for egocentric photo streams segmentation"
    - "dockerface an easy to install and use faster r cnn face detector in a docker container"
    - "an overview of multi task learning in deep neural networks"
    - "with whom do i interact detecting social interactions in egocentric photo streams"
    - "deep residual learning for image recognition"

Connected through hyperedge HE-4 (induced by source paper "batch based activity recognition from egocentric photo streams revisited"):
  with members:
    - "recognizing activities of daily living from egocentric images"
    - "batch based activity recognition from egocentric photo streams"
    - "sr clustering semantic regularized clustering for egocentric photo streams segmentation"
    - "going deeper into first person activity recognition"
    - "beyond short snippets deep networks for video classification"
    - "deep residual learning for image recognition"
    - "predicting daily activities from egocentric images using deep learning"
    - "rethinking the inception architecture for computer vision"

Connected through hyperedge HE-5 (induced by source paper "predicting visual context for unsupervised event segmentation in continuous photo streams"):
  with members:
    - "phd gifs personalized highlight detection for automatic gif creation"
    - "egocentric video description based on temporally linked sequences"
    - "sr clustering semantic regularized clustering for egocentric photo streams segmentation"
    - "hierarchically attentive rnn for album summarization and storytelling"
    - "compact cnn for indexing egocentric videos"
    - "discovering picturesque highlights from egocentric vacation videos"
    - "unsupervised learning of video representations using lstms"
    - "predicting important objects for egocentric video summarization"

Connected through hyperedge HE-6 (induced by source paper "macnet multi scale atrous convolution networks for food places classification in egocentric photo streams"):
  with members:
    - "a robust adaptive stochastic gradient method for deep learning"
    - "sr clustering semantic regularized clustering for egocentric photo streams segmentation"
    - "rethinking atrous convolution for semantic image segmentation"
    - "deeplab semantic image segmentation with deep convolutional nets atrous convolution and fully connected crfs"
    - "deep residual learning for image recognition"

Connected through hyperedge HE-7 (induced by source paper "smartphone picture organization a hierarchical approach"):
  with members:
    - "complex event recognition from images with few training examples"
    - "semantic summarization of egocentric photo stream events"
    - "you only look once unified real time object detection"
    - "image labeling on a network using social network metadata for image classification"

Connected through hyperedge HE-8 (induced by source paper "egocentric video description based on temporally linked sequences"):
  with members:
    - "batch based activity recognition from egocentric photo streams"
    - "hierarchical lstm with adjusted temporal attention for video captioning"
    - "learning to remember rare events"
    - "dense captioning events in videos"
    - "sr clustering semantic regularized clustering for egocentric photo streams segmentation"
    - "semantic summarization of egocentric photo stream events"
    - "attention based multimodal fusion for video description"
    - "video description using bidirectional recurrent neural networks"

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)