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: "automatic face reenactment"
  Abstract: We propose an image-based, facial reenactment system that replaces the face of an actor in an existing target video with the face of a user from a source video, while preserving the original target performance. Our system is fully automatic and does not require a database of source expressions. Instead, it is able to produce convincing reenactment results from a short source video captured with an off-the-shelf camera, such as a webcam, where the user performs arbitrary facial gestures. Our reenactment pipeline is conceived as part image retrieval and part face transfer: The image retrieval is based on temporal clustering of target frames and a novel image matching metric that combines appearance and motion to select candidate frames from the source video, while the face transfer uses a 2D warping strategy that preserves the user's identity. Our system excels in simplicity as it does not rely on a 3D face model, it is robust under head motion and does not require the source and target performance to be similar. We show convincing reenactment results for videos that we recorded ourselves and for low-quality footage taken from the Internet.

Connected through hyperedge HE-1 (induced by source paper "exploiting human social cognition for the detection of fake and fraudulent faces via memory networks"):
  with members:
    - "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"
    - "sophie an attentive gan for predicting paths compliant to social and physical constraints"
    - "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"
    - "pedestrian trajectory prediction with structured memory hierarchies"

Connected through hyperedge HE-2 (induced by source paper "a neural virtual anchor synthesizer based on seq2seq and gan models"):
  with members:
    - "video synthesis of human upper body with realistic face"
    - "recycle gan unsupervised video retargeting"
    - "deep contextualized word representations"
    - "reenactgan learning to reenact faces via boundary transfer"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "a style based generator architecture for generative adversarial networks"
    - "everybody dance now"
    - "attention is all you need"

Connected through hyperedge HE-3 (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-4 (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"
    - "visemenet audio driven animator centric speech animation"
    - "unsupervised training for 3d morphable model regression"
    - "a hybrid model for identity obfuscation by face replacement"
    - "everybody dance now"

Connected through hyperedge HE-5 (induced by source paper "all in one facial expression transfer editing and recognition using a single network"):
  with members:
    - "explicit facial expression transfer via fine grained semantic representations"
    - "facial expression recognition using human to animated character expression translation"
    - "dynamic facial expression generation on hilbert hypersphere with conditional wasserstein generative adversarial nets"
    - "facial expression recognition using disentangled adversarial learning"
    - "xgan unsupervised image to image translation for many to many mappings"
    - "drit diverse image to image translation via disentangled representations"
    - "geometry guided adversarial facial expression synthesis"
    - "age progression regression by conditional adversarial autoencoder"

Connected through hyperedge HE-6 (induced by source paper "explicit facial expression transfer via fine grained semantic representations"):
  with members:
    - "pluralistic image completion"
    - "deep adaptive attention for joint facial action unit detection and face alignment"
    - "spectral normalization for generative adversarial networks"
    - "ganimation anatomically aware facial animation from a single image"
    - "drit diverse image to image translation via disentangled representations"
    - "geometry guided adversarial facial expression synthesis"
    - "exprgan facial expression editing with controllable expression intensity"
    - "unpaired image to image translation using cycle consistent adversarial networks"

Connected through hyperedge HE-7 (induced by source paper "unconstrained facial expression transfer using style based generator"):
  with members:
    - "a unified feature disentangler for multi domain image translation and manipulation"
    - "large scale gan training for high fidelity natural image synthesis"
    - "a style based generator architecture for generative adversarial networks"
    - "progressive growing of gans for improved quality stability and variation"
    - "unrestricted facial geometry reconstruction using image to image translation"
    - "mofa model based deep convolutional face autoencoder for unsupervised monocular reconstruction"
    - "perceptual losses for real time style transfer and super resolution"
    - "semantic facial expression editing using autoencoded flow"

Connected through hyperedge HE-8 (induced by source paper "convolutional humanoid animation via deformation"):
  with members:
    - "learning symmetric and low energy locomotion"
    - "synthesizing images of humans in unseen poses"
    - "neural best buddies sparse cross domain correspondence"
    - "deepmimic example guided deep reinforcement learning of physics based character skills"
    - "everybody dance now"
    - "visual dynamics probabilistic future frame synthesis via cross convolutional networks"
    - "adam a method for stochastic optimization"

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)