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 "object discovery with a copy pasting gan"):
  Abstract: We tackle the problem of object discovery, where objects are segmented for a given input image, and the system is trained without using any direct supervision whatsoever. A novel copy-pasting GAN framework is proposed, where the generator learns to discover an object in one image by compositing it into another image such that the discriminator cannot tell that the resulting image is fake. After carefully addressing subtle issues, such as preventing the generator from `cheating', this game results in the generator learning to select objects, as copy-pasting objects is most likely to fool the discriminator. The system is shown to work well on four very different datasets, including large object appearance variations in challenging cluttered backgrounds.

Includes members:
  Member "tf replicator distributed machine learning for researchers":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "adversarial video generation on complex datasets")
  Member "inserting videos into videos":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "preserving semantic and temporal consistency for unpaired video to video translation")
  Member "monet unsupervised scene decomposition and representation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the next decade in ai four steps towards robust artificial intelligence")
  Member "unsupervised moving object detection via contextual information separation":
    also connected through other hyperedges:
      (none)
  Member "multi object representation learning with iterative variational inference":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "language as a cognitive tool to imagine goals in curiosity driven exploration")
  Member "learning to generate synthetic data via compositing":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "mixup regularization for region proposal based object detectors")
  Member "unsupervised image matching and object discovery as optimization":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "self labelling via simultaneous clustering and representation learning")
  Member "learning to segment via cut and paste":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "block annotation better image annotation for semantic segmentation with sub image decomposition")

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)