human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "detecting attended visual targets in video"):
  Abstract: We address the problem of detecting attention targets in video. Specifically, our goal is to identify where each person in each frame of a video is looking, and correctly handle the out-of-frame case. Our novel architecture effectively models the dynamic interaction between the scene and head features in order to infer time-varying attention targets. We introduce a new dataset, VideoAttentionTarget, consisting of fully-annotated video clips containing complex and dynamic patterns of real-world gaze behavior. Experiments on this dataset show that our model can effectively infer attention in videos. To further demonstrate the utility of our approach, we apply our predicted attention maps to two social gaze behavior recognition tasks, and show that the resulting classifiers significantly outperform existing methods. We achieve state-of-the-art performance on three datasets: GazeFollow (static images), VideoAttentionTarget (videos), and VideoCoAtt (videos), and obtain the first results for automatically classifying clinically-relevant gaze behavior without wearable cameras or eye trackers.

Includes members:
  Member "laeo net revisiting people looking at each other in videos":
    also connected through other hyperedges:
      (none)
  Member "extended gaze following detecting objects in videos beyond the camera field of view":
    also connected through other hyperedges:
      (none)
  Member "detecting gaze towards eyes in natural social interactions and its use in child assessment":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "facial pose estimation by deep learning from label distributions")
  Member "connecting gaze scene and attention generalized attention estimation via joint modeling of gaze and scene saliency":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "geddnet a network for gaze estimation with dilation and decomposition")
  Member "tracking gaze and visual focus of attention of people involved in social interaction":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "extended gaze following detecting objects in videos beyond the camera field of view")
  Member "quo vadis action recognition a new model and the kinetics dataset":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "transformation based adversarial video prediction on large scale data")
  Member "the kinetics human action video dataset":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "transformation based adversarial video prediction on large scale data")
  Member "ssd single shot multibox detector":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "relatext exploiting visual relationships for arbitrary shaped scene text detection with graph convolutional networks")

Question: Please tell me which class the source paper 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)