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: "you said that"
  Abstract: We present a method for generating a video of a talking face. The method takes as inputs: (i) still images of the target face, and (ii) an audio speech segment; and outputs a video of the target face lip synched with the audio. The method runs in real time and is applicable to faces and audio not seen at training time. #R##N#To achieve this we propose an encoder-decoder CNN model that uses a joint embedding of the face and audio to generate synthesised talking face video frames. The model is trained on tens of hours of unlabelled videos. #R##N#We also show results of re-dubbing videos using speech from a different person.

Connected through hyperedge HE-1 (induced by source paper "audio driven talking face video generation with learning based personalized head pose"):
  with members:
    - "realistic speech driven facial animation with gans"
    - "coloring with limited data few shot colorization via memory augmented networks"
    - "ganfit generative adversarial network fitting for high fidelity 3d face reconstruction"
    - "neural voice puppetry audio driven facial reenactment"
    - "one shot face reenactment"
    - "accurate 3d face reconstruction with weakly supervised learning from single image to image set"
    - "speech2face learning the face behind a voice"
    - "lip movements generation at a glance"

Connected through hyperedge HE-2 (induced by source paper "audio driven talking face video generation with natural head pose"):
  with members:
    - "coloring with limited data few shot colorization via memory augmented networks"
    - "few shot adversarial learning of realistic neural talking head models"
    - "one shot face reenactment"
    - "accurate 3d face reconstruction with weakly supervised learning from single image to image set"
    - "speech2face learning the face behind a voice"
    - "video to video synthesis"
    - "abstractive summarization of reddit posts with multi level memory networks"
    - "talking face generation by adversarially disentangled audio visual representation"

Connected through hyperedge HE-3 (induced by source paper "can we read speech beyond the lips rethinking roi selection for deep visual speech recognition"):
  with members:
    - "a cascade sequence to sequence model for chinese mandarin lip reading"
    - "deep audio visual speech recognition"
    - "end to end audiovisual speech recognition"
    - "looking to listen at the cocktail party a speaker independent audio visual model for speech separation"
    - "lcanet end to end lipreading with cascaded attention ctc"
    - "lrw 1000 a naturally distributed large scale benchmark for lip reading in the wild"
    - "pushing the boundaries of audiovisual word recognition using residual networks and lstms"
    - "words can shift dynamically adjusting word representations using nonverbal behaviors"

Connected through hyperedge HE-4 (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"
    - "obamanet photo realistic lip sync from text"
    - "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-5 (induced by source paper "vision infused deep audio inpainting"):
  with members:
    - "compound domain adaptation in an open world"
    - "recursive visual sound separation using minus plus net"
    - "the sound of motions"
    - "learning to localize sound source in visual scenes"
    - "lip movements generation at a glance"
    - "talking face generation by adversarially disentangled audio visual representation"
    - "looking to listen at the cocktail party a speaker independent audio visual model for speech separation"
    - "self supervised generation of spatial audio for 360 video"

Connected through hyperedge HE-6 (induced by source paper "video to video translation for visual speech synthesis"):
  with members:
    - "video to video synthesis"
    - "artistic style transfer for videos and spherical images"
    - "talking face generation by adversarially disentangled audio visual representation"
    - "multimodal unsupervised image to image translation"
    - "to create what you tell generating videos from captions"
    - "ganimation anatomically aware facial animation from a single image"
    - "began boundary equilibrium generative adversarial networks"
    - "gans trained by a two time scale update rule converge to a nash equilibrium"

Connected through hyperedge HE-7 (induced by source paper "icface interpretable and controllable face reenactment using gans"):
  with members:
    - "deep neural networks for no reference and full reference image quality assessment"
    - "facelet bank for fast portrait manipulation"
    - "seeing voices and hearing faces cross modal biometric matching"
    - "cr gan learning complete representations for multi view generation"
    - "reenactgan learning to reenact faces via boundary transfer"
    - "ganimation anatomically aware facial animation from a single image"
    - "the contextual loss for image transformation with non aligned data"
    - "which training methods for gans do actually converge"

Connected through hyperedge HE-8 (induced by source paper "hierarchical cross modal talking face generationwith dynamic pixel wise loss"):
  with members:
    - "inferring semantic layout for hierarchical text to image synthesis"
    - "generating talking face landmarks from speech"
    - "hierarchical long term video prediction without supervision"
    - "lip movements generation at a glance"
    - "talking face generation by adversarially disentangled audio visual representation"
    - "gp gan gender preserving gan for synthesizing faces from landmarks"
    - "talking face generation by conditional recurrent adversarial network"
    - "ganimation anatomically aware facial animation from a single image"

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)