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: "attention aware face hallucination via deep reinforcement learning"
  Abstract: Face hallucination is a domain-specific super-resolution problem with the goal to generate high-resolution (HR) faces from low-resolution (LR) input images. In contrast to existing methods that often learn a single patch-to-patch mapping from LR to HR images and are regardless of the contextual interdependency between patches, we propose a novel Attention-aware Face Hallucination (Attention-FH) framework which resorts to deep reinforcement learning for sequentially discovering attended patches and then performing the facial part enhancement by fully exploiting the global interdependency of the image. Specifically, in each time step, the recurrent policy network is proposed to dynamically specify a new attended region by incorporating what happened in the past. The state (i.e., face hallucination result for the whole image) can thus be exploited and updated by the local enhancement network on the selected region. The Attention-FH approach jointly learns the recurrent policy network and local enhancement network through maximizing the long-term reward that reflects the hallucination performance over the whole image. Therefore, our proposed Attention-FH is capable of adaptively personalizing an optimal searching path for each face image according to its own characteristic. Extensive experiments show our approach significantly surpasses the state-of-the-arts on in-the-wild faces with large pose and illumination variations.

Connected through hyperedge HE-1 (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"
    - "beyond face rotation global and local perception gan for photorealistic and identity preserving frontal view synthesis"
    - "fsrnet end to end learning face super resolution with facial priors"

Connected through hyperedge HE-2 (induced by source paper "joint face completion and super resolution using multi scale feature relation learning"):
  with members:
    - "facial expression restoration based on improved graph convolutional networks"
    - "fcsr gan joint face completion and super resolution via multi task learning"
    - "learning pyramid context encoder network for high quality image inpainting"
    - "geometry aware face completion and editing"
    - "graph neural networks a review of methods and applications"
    - "rain streak removal for single image via kernel guided cnn"
    - "learning a discriminative prior for blind image deblurring"
    - "cycle dehaze enhanced cyclegan for single image dehazing"

Connected through hyperedge HE-3 (induced by source paper "copy and paste gan face hallucination from shaded thumbnails"):
  with members:
    - "identity preserving face recovery from stylized portraits"
    - "image super resolution using very deep residual channel attention networks"
    - "style aggregated network for facial landmark detection"
    - "fsrnet end to end learning face super resolution with facial priors"
    - "arbitrary style transfer in real time with adaptive instance normalization"
    - "neural face editing with intrinsic image disentangling"
    - "unpaired image to image translation using cycle consistent adversarial networks"
    - "super fan integrated facial landmark localization and super resolution of real world low resolution faces in arbitrary poses with gans"

Connected through hyperedge HE-4 (induced by source paper "facial attribute capsules for noise face super resolution"):
  with members:
    - "occlusion robust face recognition based on mask learning with pairwisedifferential siamese network"
    - "efficient decision based black box adversarial attacks on face recognition"
    - "decorrelated adversarial learning for age invariant face recognition"
    - "mvf net multi view 3d face morphable model regression"
    - "orthogonal deep features decomposition for age invariant face recognition"
    - "arcface additive angular margin loss for deep face recognition"
    - "residual dense network for image super resolution"
    - "fsrnet end to end learning face super resolution with facial priors"

Connected through hyperedge HE-5 (induced by source paper "ddet dual path dynamic enhancement network for real world image super resolution"):
  with members:
    - "toward real world single image super resolution a new benchmark and a new model"
    - "lightweight feature fusion network for single image super resolution"
    - "super resolution via image adapted denoising cnns incorporating external and internal learning"
    - "pirm challenge on perceptual image enhancement on smartphones report"
    - "structure preserving image super resolution via contextualized multitask learning"
    - "enhanced deep residual networks for single image super resolution"
    - "photo realistic single image super resolution using a generative adversarial network"
    - "dynamic filter networks"

Connected through hyperedge HE-6 (induced by source paper "pixelrl fully convolutional network with reinforcement learning for image processing"):
  with members:
    - "weakly supervised video summarization by hierarchical reinforcement learning"
    - "grad cam visual explanations from deep networks via gradient based localization"
    - "chainer a deep learning framework for accelerating the research cycle"
    - "fully convolutional network with multi step reinforcement learning for image processing"
    - "ffnet video fast forwarding via reinforcement learning"
    - "distort and recover color enhancement using deep reinforcement learning"
    - "crafting a toolchain for image restoration by deep reinforcement learning"
    - "synthesizing programs for images using reinforced adversarial learning"

Connected through hyperedge HE-7 (induced by source paper "fcsr gan joint face completion and super resolution via multi task learning"):
  with members:
    - "feedback network for image super resolution"
    - "learning pyramid context encoder network for high quality image inpainting"
    - "coherent semantic attention for image inpainting"
    - "pluralistic image completion"
    - "adaptive transform domain image super resolution via orthogonally regularized deep networks"
    - "geometry aware face completion and editing"
    - "tattoo image search at scale joint detection and compact representation learning"
    - "generative image inpainting with contextual attention"

Connected through hyperedge HE-8 (induced by source paper "two phase hair image synthesis by self enhancing generative model"):
  with members:
    - "gif2video color dequantization and temporal interpolation of gif images"
    - "faceshop deep sketch based face image editing"
    - "learning dual convolutional neural networks for low level vision"
    - "esrgan enhanced super resolution generative adversarial networks"
    - "hairnet single view hair reconstruction using convolutional neural networks"
    - "residual dense network for image super resolution"
    - "video inpainting by jointly learning temporal structure and spatial details"
    - "mganet a robust model for quality enhancement of compressed video"

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)