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: "text based editing of talking head video"
  Abstract: Editing talking-head video to change the speech content or to remove filler words is challenging. We propose a novel method to edit talking-head video based on its transcript to produce a realistic output video in which the dialogue of the speaker has been modified, while maintaining a seamless audio-visual flow (i.e. no jump cuts). Our method automatically annotates an input talking-head video with phonemes, visemes, 3D face pose and geometry, reflectance, expression and scene illumination per frame. To edit a video, the user has to only edit the transcript, and an optimization strategy then chooses segments of the input corpus as base material. The annotated parameters corresponding to the selected segments are seamlessly stitched together and used to produce an intermediate video representation in which the lower half of the face is rendered with a parametric face model. Finally, a recurrent video generation network transforms this representation to a photorealistic video that matches the edited transcript. We demonstrate a large variety of edits, such as the addition, removal, and alteration of words, as well as convincing language translation and full sentence synthesis.

Connected through hyperedge HE-1 (induced by source paper "leveraging frequency analysis for deep fake image recognition"):
  with members:
    - "everybody s talkin let me talk as you want"
    - "making convolutional networks shift invariant again"
    - "learning rich features for image manipulation detection"
    - "attributing fake images to gans learning and analyzing gan fingerprints"
    - "do gans leave artificial fingerprints"
    - "tequilagan how to easily identify gan samples"
    - "spectral normalization for generative adversarial networks"
    - "detecting gan generated imagery using color cues"

Connected through hyperedge HE-2 (induced by source paper "unsupervised any to many audiovisual synthesis via exemplar autoencoders"):
  with members:
    - "stargan vc2 rethinking conditional methods for stargan based voice conversion"
    - "cyclegan vc2 improved cyclegan based non parallel voice conversion"
    - "epic fusion audio visual temporal binding for egocentric action recognition"
    - "learning individual styles of conversational gesture"
    - "speech2face learning the face behind a voice"
    - "openpose realtime multi person 2d pose estimation using part affinity fields"
    - "learning to localize sound source in visual scenes"
    - "seeing voices and hearing faces cross modal biometric matching"

Connected through hyperedge HE-3 (induced by source paper "use of a capsule network to detect fake images and videos"):
  with members:
    - "grad cam visual explanations from deep networks via gradient based localization"
    - "fsgan subject agnostic face swapping and reenactment"
    - "deferred neural rendering image synthesis using neural textures"
    - "multi task learning for detecting and segmenting manipulated facial images and videos"
    - "faceforensics learning to detect manipulated facial images"
    - "recurrent convolutional strategies for face manipulation detection in videos"
    - "domain adaptation in multi channel autoencoder based features for robust face anti spoofing"
    - "deep pixel wise binary supervision for face presentation attack detection"

Connected through hyperedge HE-4 (induced by source paper "adversarial learning of deepfakes in accounting"):
  with members:
    - "detection of accounting anomalies in the latent space using adversarial autoencoder neural networks"
    - "did you hear that adversarial examples against automatic speech recognition"
    - "voice conversion with conditional samplernn"
    - "adversarial text generation via feature mover s distance"
    - "adversarial attacks and defences a survey"
    - "rsgan face swapping and editing using face and hair representation in latent spaces"
    - "everybody dance now"
    - "threat of adversarial attacks on deep learning in computer vision a survey"

Connected through hyperedge HE-5 (induced by source paper "forbidden knowledge in machine learning reflections on the limits of research and publication"):
  with members:
    - "deferred neural rendering image synthesis using neural textures"
    - "faceforensics learning to detect manipulated facial images"
    - "artificial intelligence governance and ethics global perspectives"
    - "human detection of machine manipulated media"
    - "release strategies and the social impacts of language models"
    - "brainnet a multi person brain to brain interface for direct collaboration between brains"
    - "a replication study machine learning models are capable of predicting sexual orientation from facial images"
    - "reducing malicious use of synthetic media research considerations and potential release practices for machine learning"

Connected through hyperedge HE-6 (induced by source paper "durian duration informed attention network for multimodal synthesis"):
  with members:
    - "fastspeech fast robust and controllable text to speech"
    - "clarinet parallel wave generation in end to end text to speech"
    - "close to human quality tts with transformer"
    - "efficient neural audio synthesis"
    - "style tokens unsupervised style modeling control and transfer in end to end speech synthesis"
    - "neural speech synthesis with transformer network"
    - "hierarchical generative modeling for controllable speech synthesis"
    - "deep voice 3 scaling text to speech with convolutional sequence learning"

Connected through hyperedge HE-7 (induced by source paper "neural voice puppetry audio driven facial reenactment"):
  with members:
    - "deferred neural rendering image synthesis using neural textures"
    - "faceforensics learning to detect manipulated facial images"
    - "realistic speech driven facial animation with gans"
    - "capture learning and synthesis of 3d speaking styles"
    - "neural style preserving visual dubbing"
    - "headon real time reenactment of human portrait videos"
    - "forensictransfer weakly supervised domain adaptation for forgery detection"
    - "deep appearance models for face rendering"

Connected through hyperedge HE-8 (induced by source paper "detecting deepfake forged contents with separable convolutional neural network and image segmentation"):
  with members:
    - "learning rich features for image manipulation detection"
    - "mesonet a compact facial video forgery detection network"
    - "capsule forensics using capsule networks to detect forged images and videos"
    - "two stream neural networks for tampered face detection"
    - "a style based generator architecture for generative adversarial networks"
    - "in ictu oculi exposing ai generated fake face videos by detecting eye blinking"
    - "aligned and non aligned double jpeg detection using convolutional neural networks"
    - "xception deep learning with depthwise separable convolutions"

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)