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: "recent progress of face image synthesis"
  Abstract: Face synthesis has been a fascinating yet challenging problem in computer vision and machine learning. Its main research effort is to design algorithms to generate photo-realistic face images via given semantic domain. It has been a crucial prepossessing step of main-stream face recognition approaches and an excellent test of AI ability to use complicated probability distributions. In this paper, we provide a comprehensive review of typical face synthesis works that involve traditional methods as well as advanced deep learning approaches. Particularly, Generative Adversarial Net (GAN) is highlighted to generate photo-realistic and identity preserving results. Furthermore, the public available databases and evaluation metrics are introduced in details. We end the review with discussing unsolved difficulties and promising directions for future research.

Connected through hyperedge HE-1 (induced by source paper "privacynet semi adversarial networks for multi attribute face privacy"):
  with members:
    - "sensitivenets learning agnostic representations with application to face recognition"
    - "some research problems in biometrics the future beckons"
    - "rank consistent ordinal regression for neural networks"
    - "mitigating information leakage in image representations a maximum entropy approach"
    - "right for the right reason training agnostic networks"
    - "anonymizing k facial attributes via adversarial perturbations"
    - "a hybrid model for identity obfuscation by face replacement"
    - "gender privacy an ensemble of semi adversarial networks for confounding arbitrary gender classifiers"

Connected through hyperedge HE-2 (induced by source paper "faceforensics learning to detect manipulated facial images"):
  with members:
    - "deferred neural rendering image synthesis using neural textures"
    - "learning rich features for image manipulation detection"
    - "headon real time reenactment of human portrait videos"
    - "fighting fake news image splice detection via learned self consistency"
    - "mesonet a compact facial video forgery detection network"
    - "forensictransfer weakly supervised domain adaptation for forgery detection"
    - "faceforensics a large scale video dataset for forgery detection in human faces"
    - "two stream neural networks for tampered face detection"

Connected through hyperedge HE-3 (induced by source paper "conditional adversarial synthesis of 3d facial action units"):
  with members:
    - "srefi synthesis of realistic example face images"
    - "cnn based real time dense face reconstruction with inverse rendered photo realistic face images"
    - "exprgan facial expression editing with controllable expression intensity"
    - "multi view image generation from a single view"
    - "age progression regression by conditional adversarial autoencoder"
    - "photorealistic facial expression synthesis by the conditional difference adversarial autoencoder"
    - "infogan interpretable representation learning by information maximizing generative adversarial nets"
    - "unsupervised representation learning with deep convolutional generative adversarial networks"

Connected through hyperedge HE-4 (induced by source paper "generating photo realistic training data to improve face recognition accuracy"):
  with members:
    - "representation learning by rotating your faces"
    - "domain specific face synthesis for video face recognition from a single sample per person"
    - "training deep face recognition systems with synthetic data"
    - "privacy protective gan for face de identification"
    - "vggface2 a dataset for recognising faces across pose and age"
    - "beyond face rotation global and local perception gan for photorealistic and identity preserving frontal view synthesis"
    - "progressive growing of gans for improved quality stability and variation"
    - "face aging with conditional generative adversarial networks"

Connected through hyperedge HE-5 (induced by source paper "fast face image synthesis with minimal training"):
  with members:
    - "began boundary equilibrium generative adversarial networks"
    - "vggface2 a dataset for recognising faces across pose and age"
    - "large pose 3d face reconstruction from a single image via direct volumetric cnn regression"
    - "beyond face rotation global and local perception gan for photorealistic and identity preserving frontal view synthesis"
    - "progressive growing of gans for improved quality stability and variation"
    - "face aging with conditional generative adversarial networks"
    - "magan margin adaptation for generative adversarial networks"
    - "srefi synthesis of realistic example face images"

Connected through hyperedge HE-6 (induced by source paper "high diversity attribute guided face generation with gans"):
  with members:
    - "mcgan mean and covariance feature matching gan"
    - "began boundary equilibrium generative adversarial networks"
    - "it takes only two adversarial generator encoder networks"
    - "progressive growing of gans for improved quality stability and variation"
    - "focal loss for dense object detection"
    - "controllable generative adversarial network"
    - "face aging with conditional generative adversarial networks"
    - "image quality assessment techniques show improved training and evaluation of autoencoder generative adversarial networks"

Connected through hyperedge HE-7 (induced by source paper "improving face detection performance with 3d rendered synthetic data"):
  with members:
    - "survey of face detection on low quality images"
    - "training deep face recognition systems with synthetic data"
    - "seeing small faces from robust anchor s perspective"
    - "pyramidbox a context assisted single shot face detector"
    - "ganimation anatomically aware facial animation from a single image"
    - "sface an efficient network for face detection in large scale variations"
    - "pushing the limits of unconstrained face detection a challenge dataset and baseline results"
    - "cms rcnn contextual multi scale region based cnn for unconstrained face detection"

Connected through hyperedge HE-8 (induced by source paper "natural and effective obfuscation by head inpainting"):
  with members:
    - "person recognition in personal photo collections"
    - "gp gan gender preserving gan for synthesizing faces from landmarks"
    - "pose guided person image generation"
    - "a domain based approach to social relation recognition"
    - "segan segmenting and generating the invisible"
    - "adversarial image perturbation for privacy protection a game theory perspective"
    - "synthesizing normalized faces from facial identity features"
    - "disentangled person image generation"

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)