human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "maskgan towards diverse and interactive facial image manipulation"
  Abstract: Facial image manipulation has achieved great progresses in recent years. However, previous methods either operate on a predefined set of face attributes or leave users little freedom to interactively manipulate images. To overcome these drawbacks, we propose a novel framework termed MaskGAN, enabling diverse and interactive face manipulation. Our key insight is that semantic masks serve as a suitable intermediate representation for flexible face manipulation with fidelity preservation. MaskGAN has two main components: 1) Dense Mapping Network, and 2) Editing Behavior Simulated Training. Specifically, Dense mapping network learns style mapping between a free-form user modified mask and a target image, enabling diverse generation results. Editing behavior simulated training models the user editing behavior on the source mask, making the overall framework more robust to various manipulated inputs. To facilitate extensive studies, we construct a large-scale high-resolution face dataset with fine-grained mask annotations named CelebAMask-HQ. MaskGAN is comprehensively evaluated on two challenging tasks: attribute transfer and style copy, demonstrating superior performance over other state-of-the-art methods. The code, models and dataset are available at \url{this https URL}.

Connected through hyperedge HE-1 (induced by source paper "rotate and render unsupervised photorealistic face rotation from single view images"):
  with members:
    - "representation learning by rotating your faces"
    - "learning correspondence from the cycle consistency of time"
    - "semantic image synthesis with spatially adaptive normalization"
    - "face alignment in full pose range a 3d total solution"
    - "make a face towards arbitrary high fidelity face manipulation"
    - "learning to predict layout to image conditional convolutions for semantic image synthesis"
    - "vision infused deep audio inpainting"
    - "cr gan learning complete representations for multi view generation"

Connected through hyperedge HE-2 (induced by source paper "cooperative semantic segmentation and image restoration in adverse environmental conditions"):
  with members:
    - "spatial attentive single image deraining with a high quality real rain dataset"
    - "progressive image deraining networks a better and simpler baseline"
    - "i can see clearly now image restoration via de raining"
    - "robust semantic segmentation in adverse weather conditions by means of sensor data fusion"
    - "multi channel attention selection gan with cascaded semantic guidance for cross view image translation"
    - "single image reflection removal exploiting misaligned training data and network enhancements"
    - "bisenet bilateral segmentation network for real time semantic segmentation"
    - "semantic foggy scene understanding with synthetic data"

Connected through hyperedge HE-3 (induced by source paper "ae ot gan training gans from data specific latent distribution"):
  with members:
    - "diagnosing and enhancing vae models"
    - "large scale adversarial representation learning"
    - "generating diverse high fidelity images with vq vae 2"
    - "disconnected manifold learning for generative adversarial networks"
    - "spectral normalization for generative adversarial networks"
    - "large scale gan training for high fidelity natural image synthesis"
    - "progressive growing of gans for improved quality stability and variation"
    - "wasserstein divergence for gans"

Connected through hyperedge HE-4 (induced by source paper "towards photo realistic virtual try on by adaptively generating leftrightarrow preserving image content"):
  with members:
    - "fashion minimal edits for outfit improvement"
    - "sc fegan face editing generative adversarial network with user s sketch and color"
    - "foreground aware image inpainting"
    - "semantic image synthesis with spatially adaptive normalization"
    - "fashion editing with multi scale attention normalization"
    - "learning based animation of clothing for virtual try on"
    - "pose guided fashion image synthesis using deep generative model"
    - "toward characteristic preserving image based virtual try on network"

Connected through hyperedge HE-5 (induced by source paper "3d carigan an end to end solution to 3d caricature generation from face photos"):
  with members:
    - "carigans unpaired photo to caricature translation"
    - "carigan caricature generation through weakly paired adversarial learning"
    - "generating 3d faces using convolutional mesh autoencoders"
    - "warpgan automatic caricature generation"
    - "alive caricature from 2d to 3d"
    - "3d face reconstruction with geometry details from a single image"
    - "large pose 3d face reconstruction from a single image via direct volumetric cnn regression"
    - "deepsketch2face a deep learning based sketching system for 3d face and caricature modeling"

Connected through hyperedge HE-6 (induced by source paper "analysis of gender inequality in face recognition accuracy"):
  with members:
    - "does face recognition accuracy get better with age deep face matchers say no"
    - "an experimental evaluation of covariates effects on unconstrained face verification"
    - "characterizing the variability in face recognition accuracy relative to race"
    - "retinaface single stage dense face localisation in the wild"
    - "bisenet bilateral segmentation network for real time semantic segmentation"
    - "cosface large margin cosine loss for deep face recognition"
    - "arcface additive angular margin loss for deep face recognition"
    - "vggface2 a dataset for recognising faces across pose and age"

Connected through hyperedge HE-7 (induced by source paper "sean image synthesis with semantic region adaptive normalization"):
  with members:
    - "image2stylegan how to embed images into the stylegan latent space"
    - "controllable artistic text style transfer via shape matching gan"
    - "few shot unsupervised image to image translation"
    - "semantic image synthesis with spatially adaptive normalization"
    - "mask guided portrait editing with conditional gans"
    - "inferring semantic layout for hierarchical text to image synthesis"
    - "non stationary texture synthesis by adversarial expansion"
    - "multimodal unsupervised image to image translation"

Connected through hyperedge HE-8 (induced by source paper "disentangled makeup transfer with generative adversarial network"):
  with members:
    - "show attend and translate unsupervised image translation with self regularization and attention"
    - "bisenet bilateral segmentation network for real time semantic segmentation"
    - "drit diverse image to image translation via disentangled representations"
    - "arbitrary style transfer in real time with adaptive instance normalization"
    - "learning to discover cross domain relations with generative adversarial networks"
    - "unpaired image to image translation using cycle consistent adversarial networks"
    - "improved training of wasserstein gans"
    - "stargan unified generative adversarial networks for multi domain image to image translation"

Question: Please tell me which class the center node 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)