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: "elegant exchanging latent encodings with gan for transferring multiple face attributes"
  Abstract: Recent studies on face attribute transfer have achieved great success, especially after the emergence of generative adversarial networks (GANs). A lot of image-to-image translation models are able to transfer face attributes given an input image. However, they suffer from three limitations: (1) failing to make image generation by exemplars; (2) unable to deal with multiple face attributes simultaneously; (3) low-quality generated images, such as low resolution and sensible artifacts. To address these limitations, we propose a novel model that receives two images of different attributes as inputs. Our model can transfer the exactly same type of attributes from one image to another by exchanging certain part of their encodings. All the attributes are encoded in the latent space in a disentangled manner, which enables us to manipulate several attributes simultaneously. Besides, it can learn the residual images so as to facilitate training on higher resolution images. With the help of multi-scale discriminators for adversarial training, it can even generate high-quality images with finer details and less artifacts. We demonstrate the effectiveness of our model in overcoming the above three limitations by comparing with other methods on the CelebA face database.

Connected through hyperedge HE-1 (induced by source paper "deepfakes and beyond a survey of face manipulation and fake detection"):
  with members:
    - "deferred neural rendering image synthesis using neural textures"
    - "detecting gan generated fake images using co occurrence matrices"
    - "multi task learning for detecting and segmenting manipulated facial images and videos"
    - "recurrent convolutional strategies for face manipulation detection in videos"
    - "the deepfake detection challenge dfdc preview dataset"
    - "analyzing and improving the image quality of stylegan"
    - "fakespotter a simple baseline for spotting ai synthesized fake faces"
    - "detecting and simulating artifacts in gan fake images"

Connected through hyperedge HE-2 (induced by source paper "inducing optimal attribute representations for conditional gans"):
  with members:
    - "few shot adversarial learning of realistic neural talking head models"
    - "multi label image recognition with graph convolutional networks"
    - "stgan a unified selective transfer network for arbitrary image attribute editing"
    - "auglabel exploiting word representations to augment labels for face attribute classification"
    - "biphasic learning of gans for high resolution image to image translation"
    - "cgans with projection discriminator"
    - "inferring semantic layout for hierarchical text to image synthesis"
    - "graph neural networks a review of methods and applications"

Connected through hyperedge HE-3 (induced by source paper "cascade ef gan progressive facial expression editing with local focuses"):
  with members:
    - "suppressing uncertainties for large scale facial expression recognition"
    - "affectnet a database for facial expression valence and arousal computing in the wild"
    - "deep facial expression recognition a survey"
    - "spectral normalization for generative adversarial networks"
    - "geometry contrastive gan for facial expression transfer"
    - "large scale gan training for high fidelity natural image synthesis"
    - "ganimation anatomically aware facial animation from a single image"
    - "shift net image inpainting via deep feature rearrangement"

Connected through hyperedge HE-4 (induced by source paper "controllable descendant face synthesis"):
  with members:
    - "kinshipgan synthesizing of kinship faces from family photos by regularizing a deep face network"
    - "unsupervised holistic image generation from key local patches"
    - "beyond face rotation global and local perception gan for photorealistic and identity preserving frontal view synthesis"
    - "progressive growing of gans for improved quality stability and variation"
    - "improved training of wasserstein gans"
    - "age progression regression by conditional adversarial autoencoder"
    - "stargan unified generative adversarial networks for multi domain image to image translation"
    - "makeup like a superstar deep localized makeup transfer network"

Connected through hyperedge HE-5 (induced by source paper "unsupervised multi domain multimodal image to image translation with explicit domain constrained disentanglement"):
  with members:
    - "unsupervised domain specific deblurring via disentangled representations"
    - "edgeconnect generative image inpainting with adversarial edge learning"
    - "a unified feature disentangler for multi domain image translation and manipulation"
    - "learning to adapt structured output space for semantic segmentation"
    - "multimodal unsupervised image to image translation"
    - "crafting a toolchain for image restoration by deep reinforcement learning"
    - "the unreasonable effectiveness of deep features as a perceptual metric"
    - "residual dense network for image super resolution"

Connected through hyperedge HE-6 (induced by source paper "cmts conditional multiple trajectory synthesizer for generating safety critical driving scenarios"):
  with members:
    - "fully featured attribute transfer"
    - "a multi domain feature learning method for visual place recognition"
    - "a closed form solution to universal style transfer"
    - "online vehicle trajectory prediction using policy anticipation network and optimization based context reasoning"
    - "interpolation in generative models"
    - "nuscenes a multimodal dataset for autonomous driving"
    - "predicting vehicle behaviors over an extended horizon using behavior interaction network"
    - "interaction aware multi agent tracking and probabilistic behavior prediction via adversarial learning"

Connected through hyperedge HE-7 (induced by source paper "attribute driven spontaneous motion in unpaired image translation"):
  with members:
    - "carigans unpaired photo to caricature translation"
    - "soft gated warping gan for pose guided person image synthesis"
    - "multimodal unsupervised image to image translation"
    - "sketchygan towards diverse and realistic sketch to image synthesis"
    - "improving shape deformation in unsupervised image to image translation"
    - "instance level facial attributes transfer with geometry aware flow"
    - "semi parametric image synthesis"
    - "a style based generator architecture for generative adversarial networks"

Connected through hyperedge HE-8 (induced by source paper "semantic hierarchy emerges in the deep generative representations for scene synthesis"):
  with members:
    - "hologan unsupervised learning of 3d representations from natural images"
    - "singan learning a generative model from a single natural image"
    - "edge semantic learning strategy for layout estimation in indoor environment"
    - "ganalyze toward visual definitions of cognitive image properties"
    - "semantic image synthesis with spatially adaptive normalization"
    - "interpreting the latent space of gans for semantic face editing"
    - "3d aware scene manipulation via inverse graphics"
    - "unified perceptual parsing for scene understanding"

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)