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 "predicting the future a jointly learnt model for action anticipation"):
  Abstract: Inspired by human neurological structures for action anticipation, we present an action anticipation model that enables the prediction of plausible future actions by forecasting both the visual and temporal future. In contrast to current state-of-the-art methods which first learn a model to predict future video features and then perform action anticipation using these features, the proposed framework jointly learns to perform the two tasks, future visual and temporal representation synthesis, and early action anticipation. The joint learning framework ensures that the predicted future embeddings are informative to the action anticipation task. Furthermore, through extensive experimental evaluations we demonstrate the utility of using both visual and temporal semantics of the scene, and illustrate how this representation synthesis could be achieved through a recurrent Generative Adversarial Network (GAN) framework. Our model outperforms the current state-of-the-art methods on multiple datasets: UCF101, UCF101-24, UT-Interaction and TV Human Interaction.

Includes members:
  Member "coupled generative adversarial network for continuous fine grained action segmentation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "fine grained action segmentation using the semi supervised action gan")
  Member "action anticipation with rbf kernelized feature mapping rnn":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "spatiotemporal relationship reasoning for pedestrian intent prediction")
  Member "deep cosine metric learning for person re identification":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "gan based pose aware regulation for video based person re identification")
  Member "convolutional sequence to sequence model for human dynamics":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "dynamic multiscale graph neural networks for 3d skeleton based human motion prediction")
  Member "multi level sequence gan for group activity recognition":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "fine grained action segmentation using the semi supervised action gan")
  Member "discrimnet semi supervised action recognition from videos using generative adversarial networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "videossl semi supervised learning for video classification")
  Member "action anticipation by predicting future dynamic images":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "diverse and admissible trajectory forecasting through multimodal context understanding")
  Member "encouraging lstms to anticipate actions very early":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "ttpp temporal transformer with progressive prediction for efficient action anticipation")

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)