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 "deep video color propagation"):
  Abstract: Traditional approaches for color propagation in videos rely on some form of matching between consecutive video frames. Using appearance descriptors, colors are then propagated both spatially and temporally. These methods, however, are computationally expensive and do not take advantage of semantic information of the scene. In this work we propose a deep learning framework for color propagation that combines a local strategy, to propagate colors frame-by-frame ensuring temporal stability, and a global strategy, using semantics for color propagation within a longer range. Our evaluation shows the superiority of our strategy over existing video and image color propagation methods as well as neural photo-realistic style transfer approaches.

Includes members:
  Member "neural color transfer between images":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "mask guided portrait editing with conditional gans")
  Member "the 2017 davis challenge on video object segmentation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "mast a memory augmented self supervised tracker")
  Member "photorealistic style transfer with screened poisson equation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "imaginenet restyling apps using neural style transfer")
  Member "deep photo style transfer":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "parameter free style projection for arbitrary style transfer")
  Member "videoset a large scale compressed video quality dataset based on jnd measurement":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "sur featnet predicting the satisfied user ratio curvefor image compression with deep feature learning")
  Member "real time user guided image colorization with learned deep priors":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "chromagan adversarial picture colorization with semantic class distribution")
  Member "video frame interpolation via adaptive separable convolution":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "softmax splatting for video frame interpolation")
  Member "universal style transfer via feature transforms":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "collaborative distillation for ultra resolution universal style transfer")

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)