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: "obamanet photo realistic lip sync from text"
  Abstract: We present ObamaNet, the first architecture that generates both audio and synchronized photo-realistic lip-sync videos from any new text. Contrary to other published lip-sync approaches, ours is only composed of fully trainable neural modules and does not rely on any traditional computer graphics methods. More precisely, we use three main modules: a text-to-speech network based on Char2Wav, a time-delayed LSTM to generate mouth-keypoints synced to the audio, and a network based on Pix2Pix to generate the video frames conditioned on the keypoints.

Connected through hyperedge HE-1 (induced by source paper "photorealistic lip sync with adversarial temporal convolutional networks"):
  with members:
    - "capture learning and synthesis of 3d speaking styles"
    - "few shot adversarial learning of realistic neural talking head models"
    - "audio2face generating speech face animation from single audio with attention based bidirectional lstm networks"
    - "an empirical evaluation of generic convolutional and recurrent networks for sequence modeling"
    - "you said that"
    - "high resolution image synthesis and semantic manipulation with conditional gans"
    - "image to image translation with conditional adversarial networks"
    - "wavenet a generative model for raw audio"

Connected through hyperedge HE-2 (induced by source paper "a survey and taxonomy of adversarial neural networks for text to image synthesis"):
  with members:
    - "object driven text to image synthesis via adversarial training"
    - "how generative adversarial networks and their variants work an overview"
    - "mirrorgan learning text to image generation by redescription"
    - "dm gan dynamic memory generative adversarial networks for text to image synthesis"
    - "inferring semantic layout for hierarchical text to image synthesis"
    - "photographic text to image synthesis with a hierarchically nested adversarial network"
    - "adversarial learning of semantic relevance in text to image synthesis"
    - "mc gan multi conditional generative adversarial network for image synthesis"

Connected through hyperedge HE-3 (induced by source paper "towards automatic face to face translation"):
  with members:
    - "deep audio visual speech recognition"
    - "a baseline neural machine translation system for indian languages"
    - "massively multilingual neural machine translation"
    - "neural voice cloning with a few samples"
    - "lip movements generation at a glance"
    - "talking face generation by adversarially disentangled audio visual representation"
    - "rapid adaptation of neural machine translation to new languages"
    - "efficiently trainable text to speech system based on deep convolutional networks with guided attention"

Connected through hyperedge HE-4 (induced by source paper "animating face using disentangled audio representations"):
  with members:
    - "capture learning and synthesis of 3d speaking styles"
    - "the conversation deep audio visual speech enhancement"
    - "lip movements generation at a glance"
    - "talking face generation by adversarially disentangled audio visual representation"
    - "lrs3 ted a large scale dataset for visual speech recognition"
    - "looking to listen at the cocktail party a speaker independent audio visual model for speech separation"
    - "visemenet audio driven animator centric speech animation"
    - "speech driven facial reenactment using conditional generative adversarial networks"

Connected through hyperedge HE-5 (induced by source paper "lumierenet lecture video synthesis from audio"):
  with members:
    - "video to video synthesis"
    - "recycle gan unsupervised video retargeting"
    - "densepose dense human pose estimation in the wild"
    - "everybody dance now"
    - "infovae information maximizing variational autoencoders"
    - "unpaired image to image translation using cycle consistent adversarial networks"
    - "perceptual losses for real time style transfer and super resolution"
    - "deep feature consistent variational autoencoder"

Connected through hyperedge HE-6 (induced by source paper "talking face generation by conditional recurrent adversarial network"):
  with members:
    - "image super resolution by neural texture transfer"
    - "video to video synthesis"
    - "decoupled learning for conditional adversarial networks"
    - "lip movements generation at a glance"
    - "talking face generation by adversarially disentangled audio visual representation"
    - "dual motion gan for future flow embedded video prediction"
    - "decomposing motion and content for natural video sequence prediction"
    - "r btn cross domain face composite and synthesis from limited facial patches"

Connected through hyperedge HE-7 (induced by source paper "high resolution talking face generation via mutual information approximation"):
  with members:
    - "lip movements generation at a glance"
    - "talking face generation by adversarially disentangled audio visual representation"
    - "which training methods for gans do actually converge"
    - "speech driven facial reenactment using conditional generative adversarial networks"
    - "ensemble estimation of mutual information"
    - "recurrent scale approximation for object detection in cnn"
    - "you said that"
    - "perceptual losses for real time style transfer and super resolution"

Connected through hyperedge HE-8 (induced by source paper "a survey of comics research in computer science"):
  with members:
    - "using posters to recommend anime and mangas in a cold start scenario"
    - "comicolorization semi automatic manga colorization"
    - "sketch based manga retrieval using manga109 dataset"
    - "towards the automatic anime characters creation with generative adversarial networks"
    - "bam the behance artistic media dataset for recognition beyond photography"
    - "unpaired image to image translation using cycle consistent adversarial networks"
    - "style transfer for anime sketches with enhanced residual u net and auxiliary classifier gan"
    - "visual to sound generating natural sound for videos in the wild"

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)