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: "emerging from water underwater image color correction based on weakly supervised color transfer"
  Abstract: Underwater vision suffers from severe effects due to selective attenuation and scattering when light propagates through water. Such degradation not only affects the quality of underwater images, but limits the ability of vision tasks. Different from existing methods that either ignore the wavelength dependence on the attenuation or assume a specific spectral profile, we tackle color distortion problem of underwater images from a new view. In this letter, we propose a weakly supervised color transfer method to correct color distortion. The proposed method relaxes the need for paired underwater images for training and allows the underwater images being taken in unknown locations. Inspired by cycle-consistent adversarial networks, we design a multiterm loss function including adversarial loss, cycle consistency loss, and structural similarity index measure loss, which makes the content and structure of the outputs same as the inputs, meanwhile the color is similar to the images that were taken without the water. Experiments on underwater images captured under diverse scenes show that our method produces visually pleasing results, even outperforms the state-of-the-art methods. Besides, our method can improve the performance of vision tasks.

Connected through hyperedge HE-1 (induced by source paper "silhonet fisheye adaptation of a roi based object pose estimation network to monocular fisheye images"):
  with members:
    - "woodscape a multi task multi camera fisheye dataset for autonomous driving"
    - "underwater fish detection with weak multi domain supervision"
    - "datasets for face and object detection in fisheye images"
    - "spherical cnns on unstructured grids"
    - "spherical u net on cortical surfaces methods and applications"
    - "tagslam robust slam with fiducial markers"
    - "convolutions on spherical images"
    - "reprojection r cnn a fast and accurate object detector for 360 images"

Connected through hyperedge HE-2 (induced by source paper "domain adaptive adversarial learning based on physics model feedback for underwater image enhancement"):
  with members:
    - "an underwater image enhancement benchmark dataset and beyond"
    - "watergan unsupervised generative network to enable real time color correction of monocular underwater images"
    - "revisiting video saliency a large scale benchmark and a new model"
    - "enhancing underwater imagery using generative adversarial networks"
    - "unpaired image to image translation using cycle consistent adversarial networks"
    - "image de raining using a conditional generative adversarial network"
    - "dehazenet an end to end system for single image haze removal"
    - "photo realistic single image super resolution using a generative adversarial network"

Connected through hyperedge HE-3 (induced by source paper "diving deeper into underwater image enhancement a survey"):
  with members:
    - "all in one underwater image enhancement using domain adversarial learning"
    - "an underwater image enhancement benchmark dataset and beyond"
    - "watergan unsupervised generative network to enable real time color correction of monocular underwater images"
    - "the relativistic discriminator a key element missing from standard gan"
    - "deep underwater image enhancement"
    - "spectral normalization for generative adversarial networks"
    - "enhancing underwater imagery using generative adversarial networks"
    - "underwater single image color restoration using haze lines and a new quantitative dataset"

Connected through hyperedge HE-4 (induced by source paper "stefann scene text editor using font adaptive neural network"):
  with members:
    - "learning to read by spelling towards unsupervised text recognition"
    - "edit probability for scene text recognition"
    - "multi oriented scene text detection via corner localization and region segmentation"
    - "chinese typography transfer"
    - "east an efficient and accurate scene text detector"
    - "auto encoder guided gan for chinese calligraphy synthesis"
    - "visual attribute transfer through deep image analogy"
    - "multi content gan for few shot font style transfer"

Connected through hyperedge HE-5 (induced by source paper "an underwater image enhancement benchmark dataset and beyond"):
  with members:
    - "diving deeper into underwater image enhancement a survey"
    - "salient object detection in the deep learning era an in depth survey"
    - "nested network with two stream pyramid for salient object detection in optical remote sensing images"
    - "watergan unsupervised generative network to enable real time color correction of monocular underwater images"
    - "underwater single image color restoration using haze lines and a new quantitative dataset"
    - "an iterative co saliency framework for rgbd images"
    - "unpaired image to image translation using cycle consistent adversarial networks"
    - "photographic image synthesis with cascaded refinement networks"

Connected through hyperedge HE-6 (induced by source paper "underwater color restoration using u net denoising autoencoder"):
  with members:
    - "watergan unsupervised generative network to enable real time color correction of monocular underwater images"
    - "enhancing underwater imagery using generative adversarial networks"
    - "denoising adversarial autoencoders"
    - "unpaired image to image translation using cycle consistent adversarial networks"
    - "underwater optical image processing a comprehensive review"
    - "u net convolutional networks for biomedical image segmentation"

Connected through hyperedge HE-7 (induced by source paper "real time model based image color correction for underwater robots"):
  with members:
    - "watergan unsupervised generative network to enable real time color correction of monocular underwater images"
    - "enhancing underwater imagery using generative adversarial networks"
    - "orb slam a versatile and accurate monocular slam system"

Connected through hyperedge HE-8 (induced by source paper "deep underwater image enhancement"):
  with members:
    - "watergan unsupervised generative network to enable real time color correction of monocular underwater images"
    - "dehazenet an end to end system for single image haze removal"
    - "adam a method for stochastic optimization"

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)