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: "beyond face rotation global and local perception gan for photorealistic and identity preserving frontal view synthesis"
  Abstract: Photorealistic frontal view synthesis from a single face image has a wide range of applications in the field of face recognition. Although data-driven deep learning methods have been proposed to address this problem by seeking solutions from ample face data, this problem is still challenging because it is intrinsically ill-posed. This paper proposes a Two-Pathway Generative Adversarial Network (TP-GAN) for photorealistic frontal view synthesis by simultaneously perceiving global structures and local details. Four landmark located patch networks are proposed to attend to local textures in addition to the commonly used global encoder-decoder network. Except for the novel architecture, we make this ill-posed problem well constrained by introducing a combination of adversarial loss, symmetry loss and identity preserving loss. The combined loss function leverages both frontal face distribution and pre-trained discriminative deep face models to guide an identity preserving inference of frontal views from profiles. Different from previous deep learning methods that mainly rely on intermediate features for recognition, our method directly leverages the synthesized identity preserving image for downstream tasks like face recognition and attribution estimation. Experimental results demonstrate that our method not only presents compelling perceptual results but also outperforms state-of-the-art results on large pose face recognition.

Connected through hyperedge HE-1 (induced by source paper "rotate and render unsupervised photorealistic face rotation from single view images"):
  with members:
    - "maskgan towards diverse and interactive facial image manipulation"
    - "representation learning by rotating your faces"
    - "learning correspondence from the cycle consistency of time"
    - "semantic image synthesis with spatially adaptive normalization"
    - "face alignment in full pose range a 3d total solution"
    - "make a face towards arbitrary high fidelity face manipulation"
    - "learning to predict layout to image conditional convolutions for semantic image synthesis"
    - "vision infused deep audio inpainting"

Connected through hyperedge HE-2 (induced by source paper "fine grained image to image transformation towards visual recognition"):
  with members:
    - "a two step disentanglement method"
    - "hologan unsupervised learning of 3d representations from natural images"
    - "foreground aware image inpainting"
    - "carigan caricature generation through weakly paired adversarial learning"
    - "visual object networks image generation with disentangled 3d representation"
    - "recovering realistic texture in image super resolution by deep spatial feature transform"
    - "cr gan learning complete representations for multi view generation"
    - "multi task convolutional neural network for pose invariant face recognition"

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"
    - "elegant exchanging latent encodings with gan for transferring multiple face attributes"
    - "large scale gan training for high fidelity natural image synthesis"
    - "ganimation anatomically aware facial animation from a single image"

Connected through hyperedge HE-4 (induced by source paper "face hallucination with finishing touches"):
  with members:
    - "representation learning by rotating your faces"
    - "multi prototype networks for unconstrained set based face recognition"
    - "to learn image super resolution use a gan to learn how to do image degradation first"
    - "learning to see in the dark"
    - "non local neural networks"
    - "sphereface deep hypersphere embedding for face recognition"
    - "fsrnet end to end learning face super resolution with facial priors"
    - "attention aware face hallucination via deep reinforcement learning"

Connected through hyperedge HE-5 (induced by source paper "everybody s talkin let me talk as you want"):
  with members:
    - "transgaga geometry aware unsupervised image to image translation"
    - "example guided style consistent image synthesis from semantic labeling"
    - "disentangling content and style via unsupervised geometry distillation"
    - "neural style preserving visual dubbing"
    - "make a face towards arbitrary high fidelity face manipulation"
    - "geometry aware face completion and editing"
    - "high resolution talking face generation via mutual information approximation"
    - "lip movements generation at a glance"

Connected through hyperedge HE-6 (induced by source paper "dotfan a domain transferred face augmentation network for pose and illumination invariant face recognition"):
  with members:
    - "class balanced loss based on effective number of samples"
    - "cosface large margin cosine loss for deep face recognition"
    - "arcface additive angular margin loss for deep face recognition"
    - "pose robust face recognition via deep residual equivariant mapping"
    - "mobilenets efficient convolutional neural networks for mobile vision applications"
    - "unpaired image to image translation using cycle consistent adversarial networks"
    - "improved training of wasserstein gans"
    - "synthesizing normalized faces from facial identity features"

Connected through hyperedge HE-7 (induced by source paper "xcos an explainable cosine metric for face verification task"):
  with members:
    - "grad cam visual explanations from deep networks via gradient based localization"
    - "approximating cnns with bag of local features models works surprisingly well on imagenet"
    - "free form video inpainting with 3d gated convolution and temporal patchgan"
    - "improving the interpretability of deep neural networks with knowledge distillation"
    - "ted teaching ai to explain its decisions"
    - "arcface additive angular margin loss for deep face recognition"
    - "towards interpretable face recognition"
    - "vggface2 a dataset for recognising faces across pose and age"

Connected through hyperedge HE-8 (induced by source paper "region based adversarial synthesis of facial action units"):
  with members:
    - "conditional adversarial synthesis of 3d facial action units"
    - "deep adaptive attention for joint facial action unit detection and face alignment"
    - "deep face recognition a survey"
    - "attention gan for object transfiguration in wild images"
    - "ganimation anatomically aware facial animation from a single image"
    - "exprgan facial expression editing with controllable expression intensity"
    - "age progression regression by conditional adversarial autoencoder"
    - "eac net a region based deep enhancing and cropping approach for facial action unit detection"

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)