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: "multi view image generation from a single view"
  Abstract: This paper addresses a challenging problem -- how to generate multi-view cloth images from only a single view input. To generate realistic-looking images with different views from the input, we propose a new image generation model termed VariGANs that combines the strengths of the variational inference and the Generative Adversarial Networks (GANs). Our proposed VariGANs model generates the target image in a coarse-to-fine manner instead of a single pass which suffers from severe artifacts. It first performs variational inference to model global appearance of the object (e.g., shape and color) and produce a coarse image with a different view. Conditioned on the generated low resolution images, it then proceeds to perform adversarial learning to fill details and generate images of consistent details with the input. Extensive experiments conducted on two clothing datasets, MVC and DeepFashion, have demonstrated that images of a novel view generated by our model are more plausible than those generated by existing approaches, in terms of more consistent global appearance as well as richer and sharper details.

Connected through hyperedge HE-1 (induced by source paper "deep portrait image completion and extrapolation"):
  with members:
    - "synthesizing images of humans in unseen poses"
    - "look into person joint body parsing pose estimation network and a new benchmark"
    - "everybody dance now"
    - "generative image inpainting with contextual attention"
    - "gans trained by a two time scale update rule converge to a nash equilibrium"
    - "look into person self supervised structure sensitive learning and a new benchmark for human parsing"
    - "generative face completion"
    - "a generative model of people in clothing"

Connected through hyperedge HE-2 (induced by source paper "dual encoder decoder based generative adversarial networks for disentangled facial representation learning"):
  with members:
    - "representation learning by rotating your faces"
    - "began boundary equilibrium generative adversarial networks"
    - "gans trained by a two time scale update rule converge to a nash equilibrium"
    - "attgan facial attribute editing by only changing what you want"
    - "beyond face rotation global and local perception gan for photorealistic and identity preserving frontal view synthesis"
    - "reconstruction based disentanglement for pose invariant face recognition"
    - "progressive growing of gans for improved quality stability and variation"
    - "generative face completion"

Connected through hyperedge HE-3 (induced by source paper "can adversarial networks hallucinate occluded people with a plausible aspect"):
  with members:
    - "occluded person re identification"
    - "learning to detect and track visible and occluded body joints in a virtual world"
    - "densepose dense human pose estimation in the wild"
    - "perceptual adversarial networks for image to image transformation"
    - "beyond face rotation global and local perception gan for photorealistic and identity preserving frontal view synthesis"
    - "a generative model of people in clothing"
    - "deblurgan blind motion deblurring using conditional adversarial networks"
    - "hydraplus net attentive deep features for pedestrian analysis"

Connected through hyperedge HE-4 (induced by source paper "appearance and pose conditioned human image generation using deformable gans"):
  with members:
    - "synthesizing images of humans in unseen poses"
    - "dense pose transfer"
    - "low shot learning from imaginary data"
    - "densepose dense human pose estimation in the wild"
    - "a discriminatively learned cnn embedding for person reidentification"
    - "a generative model of people in clothing"
    - "natural and effective obfuscation by head inpainting"
    - "deformable gans for pose based human image generation"

Connected through hyperedge HE-5 (induced by source paper "attention based fusion for multi source human image generation"):
  with members:
    - "neural rendering and reenactment of human actor videos"
    - "soft gated warping gan for pose guided person image synthesis"
    - "synthesizing images of humans in unseen poses"
    - "mc gan multi conditional generative adversarial network for image synthesis"
    - "the perception distortion tradeoff"
    - "a variational u net for conditional appearance and shape generation"
    - "dense pose transfer"
    - "dynamic few shot visual learning without forgetting"

Connected through hyperedge HE-6 (induced by source paper "conditional adversarial synthesis of 3d facial action units"):
  with members:
    - "recent progress of face image synthesis"
    - "srefi synthesis of realistic example face images"
    - "cnn based real time dense face reconstruction with inverse rendered photo realistic face images"
    - "exprgan facial expression editing with controllable expression intensity"
    - "age progression regression by conditional adversarial autoencoder"
    - "photorealistic facial expression synthesis by the conditional difference adversarial autoencoder"
    - "infogan interpretable representation learning by information maximizing generative adversarial nets"
    - "unsupervised representation learning with deep convolutional generative adversarial networks"

Connected through hyperedge HE-7 (induced by source paper "unsupervised geometry aware representation for 3d human pose estimation"):
  with members:
    - "multi view consistency as supervisory signal for learning shape and pose prediction"
    - "learning monocular 3d human pose estimation from multi view images"
    - "unsupervised learning of object frames by dense equivariant image labelling"
    - "adversarial inverse graphics networks learning 2d to 3d lifting and image to image translation from unpaired supervision"
    - "transformation grounded image generation network for novel 3d view synthesis"
    - "unsupervised domain adaptation for 3d keypoint estimation via view consistency"
    - "learning a multi view stereo machine"
    - "lifting from the deep convolutional 3d pose estimation from a single image"

Connected through hyperedge HE-8 (induced by source paper "synthesizing images of humans in unseen poses"):
  with members:
    - "deep view morphing"
    - "transformation grounded image generation network for novel 3d view synthesis"
    - "inferring and executing programs for visual reasoning"
    - "pose guided person image generation"
    - "a generative model of people in clothing"
    - "convolutional pose machines"
    - "fusionnet a deep fully residual convolutional neural network for image segmentation in connectomics"
    - "stacked hourglass networks for human pose estimation"

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)