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: "gesturegan for hand gesture to gesture translation in the wild"
  Abstract: Hand gesture-to-gesture translation in the wild is a challenging task since hand gestures can have arbitrary poses, sizes, locations and self-occlusions. Therefore, this task requires a high-level understanding of the mapping between the input source gesture and the output target gesture. To tackle this problem, we propose a novel hand Gesture Generative Adversarial Network (GestureGAN). GestureGAN consists of a single generator $G$ and a discriminator $D$, which takes as input a conditional hand image and a target hand skeleton image. GestureGAN utilizes the hand skeleton information explicitly, and learns the gesture-to-gesture mapping through two novel losses, the color loss and the cycle-consistency loss. The proposed color loss handles the issue of "channel pollution" while back-propagating the gradients. In addition, we present the Fr\'echet ResNet Distance (FRD) to evaluate the quality of generated images. Extensive experiments on two widely used benchmark datasets demonstrate that the proposed GestureGAN achieves state-of-the-art performance on the unconstrained hand gesture-to-gesture translation task. Meanwhile, the generated images are in high-quality and are photo-realistic, allowing them to be used as data augmentation to improve the performance of a hand gesture classifier. Our model and code are available at this https URL

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 "first order motion model for image animation"):
  with members:
    - "textured neural avatars"
    - "few shot adversarial learning of realistic neural talking head models"
    - "dwnet dense warp based network for pose guided human video generation"
    - "dual generator generative adversarial networks for multi domain image to image translation"
    - "gesture to gesture translation in the wild via category independent conditional maps"
    - "3d guided fine grained face manipulation"
    - "video to video synthesis"
    - "learning to forecast and refine residual motion for image to video generation"

Connected through hyperedge HE-3 (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-4 (induced by source paper "local class specific and global image level generative adversarial networks for semantic guided scene generation"):
  with members:
    - "seeing what a gan cannot generate"
    - "progressive pose attention transfer for person image generation"
    - "a layer based sequential framework for scene generation with gans"
    - "bridging the domain gap for ground to aerial image matching"
    - "singan learning a generative model from a single natural image"
    - "autogan neural architecture search for generative adversarial networks"
    - "coco gan generation by parts via conditional coordinating"
    - "few shot unsupervised image to image translation"

Connected through hyperedge HE-5 (induced by source paper "multi channel attention selection gan with cascaded semantic guidance for cross view image translation"):
  with members:
    - "attribute guided sketch generation"
    - "attention guided generative adversarial networks for unsupervised image to image translation"
    - "dual generator generative adversarial networks for multi domain image to image translation"
    - "soft gated warping gan for pose guided person image synthesis"
    - "cross view image synthesis using conditional gans"
    - "novel view synthesis for large scale scene using adversarial loss"
    - "attention gan for object transfiguration in wild images"
    - "dense pose transfer"

Connected through hyperedge HE-6 (induced by source paper "attentiongan unpaired image to image translation using attention guided generative adversarial networks"):
  with members:
    - "show attend and translate unsupervised image translation with self regularization and attention"
    - "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"
    - "attention guided generative adversarial networks for unsupervised image to image translation"
    - "dual generator generative adversarial networks for multi domain image to image translation"
    - "mix and match networks encoder decoder alignment for zero pair image translation"
    - "multimodal unsupervised image to image translation"
    - "attention gan for object transfiguration in wild images"

Connected through hyperedge HE-7 (induced by source paper "dual generator generative adversarial networks for multi domain image to image translation"):
  with members:
    - "every smile is unique landmark guided diverse smile generation"
    - "dual discriminator generative adversarial nets"
    - "transformation grounded image generation network for novel 3d view synthesis"
    - "loss sensitive generative adversarial networks on lipschitz densities"
    - "gans trained by a two time scale update rule converge to a nash equilibrium"
    - "pose guided person image generation"
    - "generative face completion"
    - "combogan unrestrained scalability for image domain translation"

Connected through hyperedge HE-8 (induced by source paper "unified generative adversarial networks for controllable image to image translation"):
  with members:
    - "attribute guided sketch generation"
    - "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"
    - "semantic image synthesis with spatially adaptive normalization"
    - "dual generator generative adversarial networks for multi domain image to image translation"
    - "cross view image synthesis using conditional gans"
    - "sketchygan towards diverse and realistic sketch to image synthesis"
    - "large scale gan training for high fidelity natural image synthesis"

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)