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 "the liar s walk detecting deception with gait and gesture"):
  Abstract: We present a data-driven deep neural algorithm for detecting deceptive walking behavior using nonverbal cues like gaits and gestures. We conducted an elaborate user study, where we recorded many participants performing tasks involving deceptive walking. We extract the participants' walking gaits as series of 3D poses. We annotate various gestures performed by participants during their tasks. Based on the gait and gesture data, we train an LSTM-based deep neural network to obtain deep features. Finally, we use a combination of psychology-based gait, gesture, and deep features to detect deceptive walking with an accuracy of 93.4%. This is an improvement of 16.1% over handcrafted gait and gesture features and an improvement of 5.9% and 10.1% over classifiers based on the state-of-the-art emotion and action classification algorithms, respectively. Additionally, we present a novel dataset, DeceptiveWalk, that contains gaits and gestures with their associated deception labels. To the best of our knowledge, ours is the first algorithm to detect deceptive behavior using non-verbal cues of gait and gesture.

Includes members:
  Member "anomaly detection in video sequence with appearance motion correspondence":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "self trained deep ordinal regression for end to end video anomaly detection")
  Member "learning regularity in skeleton trajectories for anomaly detection in videos":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "3d resnet with ranking loss function for abnormal activity detection in videos")
  Member "context aware emotion recognition networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "two stream aural visual affect analysis in the wild")
  Member "step spatial temporal graph convolutional networks for emotion perception from gaits":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "emoticon context aware multimodal emotion recognition using frege s principle")
  Member "gait recognition via disentangled representation learning":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "hi cmd hierarchical cross modality disentanglement for visible infrared person re identification")
  Member "identifying emotions from walking using affective and deep features":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "emoticon context aware multimodal emotion recognition using frege s principle")
  Member "pose guided human video generation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "adversarial video generation on complex datasets")
  Member "real world anomaly detection in surveillance videos":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "centrality graph convolutional networks for skeleton based action recognition")

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)