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 "background matting"):
  Abstract: The current state of the art alpha matting methods mainly rely on the trimap as the secondary and only guidance to estimate alpha. This paper investigates the effects of utilising the background information as well as trimap in the process of alpha calculation. To achieve this goal, a state of the art method, AlphaGan is adopted and modified to process the background information as an extra input channel. Extensive experiments are performed to analyse the effect of the background information in image and video matting such as training with mildly and heavily distorted backgrounds. Based on the quantitative evaluations performed on Adobe Composition-1k dataset, the proposed pipeline significantly outperforms the state of the art methods using AlphaMatting benchmark metrics.

Includes members:
  Member "deep flow guided video inpainting":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "carafe content aware reassembly of features")
  Member "deep video inpainting":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "motion excited sampler video adversarial attack with sparked prior")
  Member "free form video inpainting with 3d gated convolution and temporal patchgan":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "gated texture cnn for efficient and configurable image denoising")
  Member "inductive guided filter real time deep image matting with weakly annotated masks on mobile devices":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "natural image matting via guided contextual attention")
  Member "indices matter learning to index for deep image matting":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "alignseg feature aligned segmentation networks")
  Member "disentangled image matting":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "f b alpha matting")
  Member "alphagan generative adversarial networks for natural image matting":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "natural image matting via guided contextual attention")
  Member "deep image matting":
    also connected through other hyperedges:
      - Hyperedge HE-8 (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)