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 "multi channel attention selection gans for guided image to image translation"):
  Abstract: We propose a novel model named Multi-Channel Attention Selection Generative Adversarial Network (SelectionGAN) for guided image-to-image translation, where we translate an input image into another while respecting an external semantic guidance. The proposed SelectionGAN explicitly utilizes the semantic guidance information and consists of two stages. In the first stage, the input image and the conditional semantic guidance are fed into a cycled semantic-guided generation network to produce initial coarse results. In the second stage, we refine the initial results by using the proposed multi-scale spatial pooling \& channel selection module and the multi-channel attention selection module. Moreover, uncertainty maps automatically learned from attention maps are used to guide the pixel loss for better network optimization. Exhaustive experiments on four challenging guided image-to-image translation tasks (face, hand, body and street view) demonstrate that our SelectionGAN is able to generate significantly better results than the state-of-the-art methods. Meanwhile, the proposed framework and modules are unified solutions and can be applied to solve other generation tasks, such as semantic image synthesis. The code is available at this https URL.

Includes members:
  Member "progressive pose attention transfer for person image generation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "deep image spatial transformation for person image generation")
  Member "local class specific and global image level generative adversarial networks for semantic guided scene generation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "image to image translation with text guidance")
  Member "example guided style consistent image synthesis from semantic labeling":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "everybody s talkin let me talk as you want")
  Member "asymmetric generative adversarial networks for image to image translation":
    also connected through other hyperedges:
      (none)
  Member "u gat it unsupervised generative attentional networks with adaptive layer instance normalization for image to image translation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "augmented cyclic consistency regularization for unpaired image to image translation")
  Member "multi channel attention selection gan with cascaded semantic guidance for cross view image translation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "cooperative semantic segmentation and image restoration in adverse environmental conditions")
  Member "cycle in cycle generative adversarial networks for keypoint guided image generation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "deep image spatial transformation for person image generation")
  Member "attentiongan unpaired image to image translation using attention guided generative adversarial networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "local class specific and global image level generative adversarial networks for semantic guided scene generation")

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)