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 "language guided fashion image manipulation with feature wise transformations"):
  Abstract: Developing techniques for editing an outfit image through natural sentences and accordingly generating new outfits has promising applications for art, fashion and design. However, it is considered as a certainly challenging task since image manipulation should be carried out only on the relevant parts of the image while keeping the remaining sections untouched. Moreover, this manipulation process should generate an image that is as realistic as possible. In this work, we propose FiLMedGAN, which leverages feature-wise linear modulation (FiLM) to relate and transform visual features with natural language representations without using extra spatial information. Our experiments demonstrate that this approach, when combined with skip connections and total variation regularization, produces more plausible results than the baseline work, and has a better localization capability when generating new outfits consistent with the target description.

Includes members:
  Member "recovering realistic texture in image super resolution by deep spatial feature transform":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "perceptual image super resolution with progressive adversarial network")
  Member "da gan instance level image translation by deep attention generative adversarial networks with supplementary materials":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "deepcloud the application of a data driven generative model in design")
  Member "photographic text to image synthesis with a hierarchically nested adversarial network":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "adversarial code learning for image generation")
  Member "unsupervised person image synthesis in arbitrary poses":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "neural human video rendering joint learning of dynamic textures and rendering to video translation")
  Member "learning to color from language":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "expressing visual relationships via language")
  Member "a variational u net for conditional appearance and shape generation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "multi channel attention selection gans for guided image to image translation")
  Member "attention aware generative adversarial networks ata gans":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "attentiongan unpaired image to image translation using attention guided generative adversarial networks")
  Member "viton an image based virtual try on network":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "learning to transfer texture from clothing images to 3d humans")

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)