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: "rsgan face swapping and editing using face and hair representation in latent spaces"
  Abstract: In this paper, we present an integrated system for automatically generating and editing face images through face swapping, attribute-based editing, and random face parts synthesis. The proposed system is based on a deep neural network that variationally learns the face and hair regions with large-scale face image datasets. Different from conventional variational methods, the proposed network represents the latent spaces individually for faces and hairs. We refer to the proposed network as region-separative generative adversarial network (RSGAN). The proposed network independently handles face and hair appearances in the latent spaces, and then, face swapping is achieved by replacing the latent-space representations of the faces, and reconstruct the entire face image with them. This approach in the latent space robustly performs face swapping even for images which the previous methods result in failure due to inappropriate fitting or the 3D morphable models. In addition, the proposed system can further edit face-swapped images with the same network by manipulating visual attributes or by composing them with randomly generated face or hair parts.

Connected through hyperedge HE-1 (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"
    - "everybody dance now"
    - "threat of adversarial attacks on deep learning in computer vision a survey"

Connected through hyperedge HE-2 (induced by source paper "fsgan subject agnostic face swapping and reenactment"):
  with members:
    - "faceforensics learning to detect manipulated facial images"
    - "cr gan learning complete representations for multi view generation"
    - "reenactgan learning to reenact faces via boundary transfer"
    - "triple consistency loss for pairing distributions in gan based face synthesis"
    - "ganimation anatomically aware facial animation from a single image"
    - "fsnet an identity aware generative model for image based face swapping"
    - "vggface2 a dataset for recognising faces across pose and age"
    - "progressive growing of gans for improved quality stability and variation"

Connected through hyperedge HE-3 (induced by source paper "using photorealistic face synthesis and domain adaptation to improve facial expression analysis"):
  with members:
    - "learn to synthesize and synthesize to learn"
    - "elegant exchanging latent encodings with gan for transferring multiple face attributes"
    - "beyond face rotation global and local perception gan for photorealistic and identity preserving frontal view synthesis"
    - "learning to discover cross domain relations with generative adversarial networks"
    - "unpaired image to image translation using cycle consistent adversarial networks"
    - "improved training of wasserstein gans"
    - "stargan unified generative adversarial networks for multi domain image to image translation"
    - "fader networks manipulating images by sliding attributes"

Connected through hyperedge HE-4 (induced by source paper "faceshifter towards high fidelity and occlusion aware face swapping"):
  with members:
    - "fsgan subject agnostic face swapping and reenactment"
    - "deferred neural rendering image synthesis using neural textures"
    - "faceforensics learning to detect manipulated facial images"
    - "semantic image synthesis with spatially adaptive normalization"
    - "joint face detection and facial motion retargeting for multiple faces"
    - "arcface additive angular margin loss for deep face recognition"
    - "towards open set identity preserving face synthesis"
    - "a style based generator architecture for generative adversarial networks"

Connected through hyperedge HE-5 (induced by source paper "swapped face detection using deep learning and subjective assessment"):
  with members:
    - "grad cam visual explanations from deep networks via gradient based localization"
    - "faceforensics learning to detect manipulated facial images"
    - "approximate ranking from pairwise comparisons"
    - "deepfakes a new threat to face recognition assessment and detection"
    - "fast face swap using convolutional neural networks"
    - "deep learning in neural networks"

Connected through hyperedge HE-6 (induced by source paper "on hallucinating context and background pixels from a face mask using multi scale gans"):
  with members:
    - "sc fegan face editing generative adversarial network with user s sketch and color"
    - "edgeconnect generative image inpainting with adversarial edge learning"
    - "faceshop deep sketch based face image editing"
    - "fast face image synthesis with minimal training"
    - "identity preserving face completion for large ocular region occlusion"
    - "unified perceptual parsing for scene understanding"
    - "high resolution face completion with multiple controllable attributes via fully end to end progressive generative adversarial networks"
    - "the unreasonable effectiveness of deep features as a perceptual metric"

Connected through hyperedge HE-7 (induced by source paper "texture deformation based generative adversarial networks for face editing"):
  with members:
    - "deforming autoencoders unsupervised disentangling of shape and appearance"
    - "multimodal unsupervised image to image translation"
    - "mask aware photorealistic face attribute manipulation"
    - "elegant exchanging latent encodings with gan for transferring multiple face attributes"
    - "dna gan learning disentangled representations from multi attribute images"
    - "beyond face rotation global and local perception gan for photorealistic and identity preserving frontal view synthesis"
    - "neural face editing with intrinsic image disentangling"
    - "unpaired image to image translation using cycle consistent adversarial networks"

Connected through hyperedge HE-8 (induced by source paper "fsnet an identity aware generative model for image based face swapping"):
  with members:
    - "high resolution face completion with multiple controllable attributes via fully end to end progressive generative adversarial networks"
    - "towards open set identity preserving face synthesis"
    - "cvae gan fine grained image generation through asymmetric training"
    - "do we really need to collect millions of faces for effective face recognition"
    - "improved techniques for training gans"
    - "image to image translation with conditional adversarial networks"
    - "pyramid scene parsing network"
    - "fast face swap using convolutional neural networks"

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)