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 "emotion recognition for in the wild videos"):
  Abstract: This paper is a brief introduction to our submission to the seven basic expression classification track of Affective Behavior Analysis in-the-wild Competition held in conjunction with the IEEE International Conference on Automatic Face and Gesture Recognition (FG) 2020. Our method combines Deep Residual Network (ResNet) and Bidirectional Long Short-Term Memory Network (BLSTM), achieving 64.3% accuracy and 43.4% final metric on the validation set.

Includes members:
  Member "analysing affective behavior in the first abaw 2020 competition":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "two stream aural visual affect analysis in the wild")
  Member "expression affect action unit recognition aff wild2 multi task learning and arcface":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "lossless attention in convolutional networks for facial expression recognition in the wild")
  Member "affectnet a database for facial expression valence and arousal computing in the wild":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "cascade ef gan progressive facial expression editing with local focuses")
  Member "retinaface single stage dense face localisation in the wild":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "generalizing face representation with unlabeled data")
  Member "deep affect prediction in the wild aff wild database and challenge deep architectures and beyond":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "lossless attention in convolutional networks for facial expression recognition in the wild")
  Member "pytorch an imperative style high performance deep learning library":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "discrimination aware network pruning for deep model compression")
  Member "a multi task learning generation framework valence arousal action units primary expressions":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "analysing affective behavior in the first abaw 2020 competition")
  Member "aff wild2 extending the aff wild database for affect recognition":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "lossless attention in convolutional networks for facial expression recognition in the wild")

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)