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: "fast face swap using convolutional neural networks"
  Abstract: We consider the problem of face swapping in images, where an input identity is transformed into a target identity while preserving pose, facial expression, and lighting. To perform this mapping, we use convolutional neural networks trained to capture the appearance of the target identity from an unstructured collection of his/her photographs.This approach is enabled by framing the face swapping problem in terms of style transfer, where the goal is to render an image in the style of another one. Building on recent advances in this area, we devise a new loss function that enables the network to produce highly photorealistic results. By combining neural networks with simple pre- and post-processing steps, we aim at making face swap work in real-time with no input from the user.

Connected through hyperedge HE-1 (induced by source paper "celeb df a large scale challenging dataset for deepfake forensics"):
  with members:
    - "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"
    - "the deepfake detection challenge dfdc preview dataset"
    - "hybrid lstm and encoder decoder architecture for detection of image forgeries"
    - "use of a capsule network to detect fake images and videos"
    - "learning rich features for image manipulation detection"
    - "mesonet a compact facial video forgery detection network"

Connected through hyperedge HE-2 (induced by source paper "swaptext image based texts transfer in scenes"):
  with members:
    - "controllable artistic text style transfer via shape matching gan"
    - "ga dan geometry aware domain adaptation network for scene text detection and recognition"
    - "symmetry constrained rectification network for scene text recognition"
    - "arbitrary style transfer with style attentional networks"
    - "textsnake a flexible representation for detecting text of arbitrary shapes"
    - "verisimilar image synthesis for accurate detection and recognition of texts in scenes"
    - "spatial fusion gan for image synthesis"
    - "image inpainting via generative multi column convolutional neural networks"

Connected through hyperedge HE-3 (induced by source paper "cycle in cycle generative adversarial networks for keypoint guided image generation"):
  with members:
    - "multi channel attention selection gan with cascaded semantic guidance for cross view image translation"
    - "gazecorrection self guided eye manipulation in the wild using self supervised generative adversarial networks"
    - "semantic image synthesis with spatially adaptive normalization"
    - "cascade attention guided residue learning gan for cross modal translation"
    - "attention guided generative adversarial networks for unsupervised image to image translation"
    - "dual generator generative adversarial networks for multi domain image to image translation"
    - "video to video synthesis"
    - "cross view image synthesis using conditional gans"

Connected through hyperedge HE-4 (induced by source paper "facial synthesis from visual attributes via sketch using multi scale generators"):
  with members:
    - "polarimetric thermal to visible face verification via attribute preserved synthesis"
    - "photographic text to image synthesis with a hierarchically nested adversarial network"
    - "gp gan gender preserving gan for synthesizing faces from landmarks"
    - "face synthesis from visual attributes via sketch using conditional vaes and gans"
    - "on hallucinating context and background pixels from a face mask using multi scale gans"
    - "gans trained by a two time scale update rule converge to a nash equilibrium"
    - "modulating early visual processing by language"
    - "decomposing motion and content for natural video sequence prediction"

Connected through hyperedge HE-5 (induced by source paper "live face de identification in video"):
  with members:
    - "feature denoising for improving adversarial robustness"
    - "privacy protective gan for face de identification"
    - "arcface additive angular margin loss for deep face recognition"
    - "multimodal unsupervised image to image translation"
    - "faceforensics a large scale video dataset for forgery detection in human faces"
    - "a hybrid model for identity obfuscation by face replacement"
    - "drit diverse image to image translation via disentangled representations"
    - "vggface2 a dataset for recognising faces across pose and age"

Connected through hyperedge HE-6 (induced by source paper "deep learning for deepfakes creation and detection"):
  with members:
    - "faceforensics learning to detect manipulated facial images"
    - "on the generalization of gan image forensics"
    - "recurrent convolutional strategies for face manipulation detection in videos"
    - "unsupervised speech representation learning using wavenet autoencoders"
    - "few shot adversarial learning of realistic neural talking head models"
    - "limits of deepfake detection a robust estimation viewpoint"
    - "exposing deep fakes using inconsistent head poses"
    - "faceforensics a large scale video dataset for forgery detection in human faces"

Connected through hyperedge HE-7 (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"
    - "text based editing of talking head video"
    - "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"

Connected through hyperedge HE-8 (induced by source paper "towards disentangled representations for human retargeting by multi view learning"):
  with members:
    - "a unified feature disentangler for multi domain image translation and manipulation"
    - "a variational u net for conditional appearance and shape generation"
    - "deep appearance models for face rendering"
    - "image to image translation for cross domain disentanglement"
    - "drit diverse image to image translation via disentangled representations"
    - "learning to discover cross domain relations with generative adversarial networks"
    - "unpaired image to image translation using cycle consistent adversarial networks"
    - "mocogan decomposing motion and content for video generation"

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)