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: "visemenet audio driven animator centric speech animation"
  Abstract: We present a novel deep-learning based approach to producing animator-centric speech motion curves that drive a JALI or standard FACS-based production face-rig, directly from input audio. Our three-stage Long Short-Term Memory (LSTM) network architecture is motivated by psycho-linguistic insights: segmenting speech audio into a stream of phonetic-groups is sufficient for viseme construction; speech styles like mumbling or shouting are strongly co-related to the motion of facial landmarks; and animator style is encoded in viseme motion curve profiles. Our contribution is an automatic real-time lip-synchronization from audio solution that integrates seamlessly into existing animation pipelines. We evaluate our results by: cross-validation to ground-truth data; animator critique and edits; visual comparison to recent deep-learning lip-synchronization solutions; and showing our approach to be resilient to diversity in speaker and language.

Connected through hyperedge HE-1 (induced by source paper "text based editing of talking head video"):
  with members:
    - "neural rendering and reenactment of human actor videos"
    - "video to video synthesis"
    - "recycle gan unsupervised video retargeting"
    - "lookingood enhancing performance capture with real time neural re rendering"
    - "unsupervised training for 3d morphable model regression"
    - "a hybrid model for identity obfuscation by face replacement"
    - "everybody dance now"
    - "progressive growing of gans for improved quality stability and variation"

Connected through hyperedge HE-2 (induced by source paper "realistic speech driven facial animation with gans"):
  with members:
    - "face alignment in full pose range a 3d total solution"
    - "lip movements generation at a glance"
    - "talking face generation by adversarially disentangled audio visual representation"
    - "generative adversarial talking head bringing portraits to life with a weakly supervised neural network"
    - "ganimation anatomically aware facial animation from a single image"
    - "in ictu oculi exposing ai generated fake face videos by detecting eye blinking"
    - "video generation from text"
    - "lipnet end to end sentence level lipreading"

Connected through hyperedge HE-3 (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"
    - "speech driven facial reenactment using conditional generative adversarial networks"
    - "everybody dance now"

Connected through hyperedge HE-4 (induced by source paper "capture learning and synthesis of 3d speaking styles"):
  with members:
    - "expressive body capture 3d hands face and body from a single image"
    - "generating 3d faces using convolutional mesh autoencoders"
    - "lip movements generation at a glance"
    - "looking to listen at the cocktail party a speaker independent audio visual model for speech separation"
    - "how far are we from solving the 2d 3d face alignment problem and a dataset of 230 000 3d facial landmarks"
    - "production level facial performance capture using deep convolutional neural networks"
    - "squad 100 000 questions for machine comprehension of text"
    - "wavenet a generative model for raw audio"

Connected through hyperedge HE-5 (induced by source paper "synthesising 3d facial motion from in the wild speech"):
  with members:
    - "online and linear time attention by enforcing monotonic alignments"
    - "lip reading sentences in the wild"
    - "joint face detection and alignment using multitask cascaded convolutional networks"
    - "effective approaches to attention based neural machine translation"
    - "delving deep into rectifiers surpassing human level performance on imagenet classification"
    - "adam a method for stochastic optimization"
    - "neural machine translation by jointly learning to align and translate"
    - "point set registration coherent point drift"

Connected through hyperedge HE-6 (induced by source paper "animation synthesis triggered by vocal mimics"):
  with members:
    - "realistic speech driven facial animation with gans"
    - "capture learning and synthesis of 3d speaking styles"

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.GR(Graphics)