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: "semantic summarization of egocentric photo stream events"
  Abstract: With the rapid increase of users of wearable cameras in recent years and of the amount of data they produce, there is a strong need for automatic retrieval and summarization techniques. This work addresses the problem of automatically summarizing egocentric photo streams captured through a wearable camera by taking an image retrieval perspective. After removing non-informative images by a new CNN-based filter, images are ranked by relevance to ensure semantic diversity and finally re-ranked by a novelty criterion to reduce redundancy. To assess the results, a new evaluation metric is proposed which takes into account the non-uniqueness of the solution. Experimental results applied on a database of 7,110 images from 6 different subjects and evaluated by experts gave 95.74% of experts satisfaction and a Mean Opinion Score of 4.57 out of 5.0.

Connected through hyperedge HE-1 (induced by source paper "smartphone picture organization a hierarchical approach"):
  with members:
    - "complex event recognition from images with few training examples"
    - "toward storytelling from visual lifelogging an overview"
    - "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-2 (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"
    - "toward storytelling from visual lifelogging an overview"
    - "sr clustering semantic regularized clustering for egocentric photo streams segmentation"
    - "attention based multimodal fusion for video description"
    - "video description using bidirectional recurrent neural networks"

Connected through hyperedge HE-3 (induced by source paper "toward storytelling from visual lifelogging an overview"):
  with members:
    - "r clustering for egocentric video segmentation"
    - "multi face tracking by extended bag of tracklets in egocentric photo streams"
    - "f formation detection individuating free standing conversational groups in images"
    - "a survey on recent advances of computer vision algorithms for egocentric video"
    - "leveraging context to support automated food recognition in restaurants"
    - "predicting daily activities from egocentric images using deep learning"
    - "sequence to sequence video to text"
    - "egocentric field of view localization using first person point of view devices"

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)