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 "controllable attention for structured layered video decomposition"):
  Abstract: The objective of this paper is to be able to separate a video into its natural layers, and to control which of the separated layers to attend to. For example, to be able to separate reflections, transparency or object motion. We make the following three contributions: (i) we introduce a new structured neural network architecture that explicitly incorporates layers (as spatial masks) into its design. This improves separation performance over previous general purpose networks for this task; (ii) we demonstrate that we can augment the architecture to leverage external cues such as audio for controllability and to help disambiguation; and (iii) we experimentally demonstrate the effectiveness of our approach and training procedure with controlled experiments while also showing that the proposed model can be successfully applied to real-word applications such as reflection removal and action recognition in cluttered scenes.

Includes members:
  Member "sim2real transfer learning for 3d pose estimation motion to the rescue":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "synthetic humans for action recognition from unseen viewpoints")
  Member "double dip unsupervised image decomposition via coupled deep image priors":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "semantic pyramid for image generation")
  Member "the conversation deep audio visual speech enhancement":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "audio visual speech enhancement using conditional variational auto encoder")
  Member "learning to localize sound source in visual scenes":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "stavis spatio temporal audiovisual saliency network")
  Member "looking to listen at the cocktail party a speaker independent audio visual model for speech separation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the state of service robots current bottlenecks in object perception and manipulation")
  Member "a short note about kinetics 600":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "transformation based adversarial video prediction on large scale data")
  Member "single image reflection removal using deep encoder decoder network":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "single image reflection removal exploiting misaligned training data and network enhancements")
  Member "single image reflection separation with perceptual losses":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "cooperative semantic segmentation and image restoration in adverse environmental conditions")

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)