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: "gp gan gender preserving gan for synthesizing faces from landmarks"
  Abstract: Facial landmarks constitute the most compressed representation of faces and are known to preserve information such as pose, gender and facial structure present in the faces. Several works exist that attempt to perform high-level face-related analysis tasks based on landmarks alone without the aid of face images. In contrast, in this work, an attempt is made to tackle the inverse problem of synthesizing faces from their respective landmarks. The primary aim of this work is to demonstrate that information preserved by landmarks (gender in particular) can be further accentuated by leveraging generative models to synthesize corresponding faces. Though the problem is particularly challenging due to its ill-posed nature, we believe that successful synthesis will enable several applications such as boosting performance of high-level face related tasks using landmark points and performing dataset augmentation. To this end, a novel face-synthesis method known as Gender Preserving Generative Adversarial Network (GP-GAN) that is guided by adversarial loss, perceptual loss and a gender preserving loss is presented. Further, we propose a novel generator sub-network UDeNet for GP-GAN that leverages advantages of U-Net and DenseNet architectures. Extensive experiments and comparison with recent methods are performed to verify the effectiveness of the proposed method. Our code is available at: https://github.com/DetionDXlGP-GAN-Gender-Preserving-GAN-for-Synthesizing-Faces-from-Landmarks

Connected through hyperedge HE-1 (induced by source paper "multi channel attention selection gans for guided image to image translation"):
  with members:
    - "progressive pose attention transfer for person image generation"
    - "local class specific and global image level generative adversarial networks for semantic guided scene generation"
    - "example guided style consistent image synthesis from semantic labeling"
    - "asymmetric generative adversarial networks for image to image translation"
    - "u gat it unsupervised generative attentional networks with adaptive layer instance normalization for image to image translation"
    - "multi channel attention selection gan with cascaded semantic guidance for cross view image translation"
    - "cycle in cycle generative adversarial networks for keypoint guided image generation"
    - "attentiongan unpaired image to image translation using attention guided generative adversarial networks"

Connected through hyperedge HE-2 (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-3 (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"
    - "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"
    - "beyond face rotation global and local perception gan for photorealistic and identity preserving frontal view synthesis"

Connected through hyperedge HE-4 (induced by source paper "recovering faces from portraits with auxiliary facial attributes"):
  with members:
    - "identity preserving face recovery from portraits"
    - "a deeper look at power normalizations"
    - "stable and controllable neural texture synthesis and style transfer using histogram losses"
    - "high quality facial photo sketch synthesis using multi adversarial networks"
    - "diversified texture synthesis with feed forward networks"
    - "unpaired image to image translation using cycle consistent adversarial networks"
    - "improved texture networks maximizing quality and diversity in feed forward stylization and texture synthesis"
    - "image de raining using a conditional generative adversarial network"

Connected through hyperedge HE-5 (induced by source paper "dafe fd density aware feature enrichment for face detection"):
  with members:
    - "face magnet magnifying feature maps to detect small faces"
    - "pushing the limits of unconstrained face detection a challenge dataset and baseline results"
    - "switching convolutional neural network for crowd counting"
    - "generating high quality crowd density maps using contextual pyramid cnns"
    - "cms rcnn contextual multi scale region based cnn for unconstrained face detection"
    - "illuminating pedestrians via simultaneous detection segmentation"
    - "high quality facial photo sketch synthesis using multi adversarial networks"
    - "single shot text detector with regional attention"

Connected through hyperedge HE-6 (induced by source paper "cross domain cascaded deep feature translation"):
  with members:
    - "transgaga geometry aware unsupervised image to image translation"
    - "logan unpaired shape transform in latent overcomplete space"
    - "augmented cyclegan learning many to many mappings from unpaired data"
    - "neural best buddies sparse cross domain correspondence"
    - "esrgan enhanced super resolution generative adversarial networks"
    - "multimodal unsupervised image to image translation"
    - "improving shape deformation in unsupervised image to image translation"
    - "free form image inpainting with gated convolution"

Connected through hyperedge HE-7 (induced by source paper "polarimetric thermal to visible face verification via self attention guided synthesis"):
  with members:
    - "polarimetric thermal to visible face verification via attribute preserved synthesis"
    - "spectral normalization for generative adversarial networks"
    - "thermal to visible synthesis of face images using multiple regions"
    - "deep cross polarimetric thermal to visible face recognition"
    - "synthesis of high quality visible faces from polarimetric thermal faces using generative adversarial networks"
    - "began boundary equilibrium generative adversarial networks"
    - "attention is all you need"
    - "high quality facial photo sketch synthesis using multi adversarial networks"

Connected through hyperedge HE-8 (induced by source paper "hierarchical cross modal talking face generationwith dynamic pixel wise loss"):
  with members:
    - "inferring semantic layout for hierarchical text to image synthesis"
    - "generating talking face landmarks from speech"
    - "hierarchical long term video prediction without supervision"
    - "lip movements generation at a glance"
    - "talking face generation by adversarially disentangled audio visual representation"
    - "talking face generation by conditional recurrent adversarial network"
    - "ganimation anatomically aware facial animation from a single image"
    - "learning hierarchical semantic image manipulation through structured representations"

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)