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: "unsupervised person image synthesis in arbitrary poses"
  Abstract: We present a novel approach for synthesizing photo-realistic images of people in arbitrary poses using generative adversarial learning. Given an input image of a person and a desired pose represented by a 2D skeleton, our model renders the image of the same person under the new pose, synthesizing novel views of the parts visible in the input image and hallucinating those that are not seen. This problem has recently been addressed in a supervised manner, i.e., during training the ground truth images under the new poses are given to the network. We go beyond these approaches by proposing a fully unsupervised strategy. We tackle this challenging scenario by splitting the problem into two principal subtasks. First, we consider a pose conditioned bidirectional generator that maps back the initially rendered image to the original pose, hence being directly comparable to the input image without the need to resort to any training image. Second, we devise a novel loss function that incorporates content and style terms, and aims at producing images of high perceptual quality. Extensive experiments conducted on the DeepFashion dataset demonstrate that the images rendered by our model are very close in appearance to those obtained by fully supervised approaches.

Connected through hyperedge HE-1 (induced by source paper "neural human video rendering joint learning of dynamic textures and rendering to video translation"):
  with members:
    - "deferred neural rendering image synthesis using neural textures"
    - "textured neural avatars"
    - "neural rendering and reenactment of human actor videos"
    - "liquid warping gan a unified framework for human motion imitation appearance transfer and novel view synthesis"
    - "dense intrinsic appearance flow for human pose transfer"
    - "video to video synthesis"
    - "openpose realtime multi person 2d pose estimation using part affinity fields"
    - "synthesizing images of humans in unseen poses"

Connected through hyperedge HE-2 (induced by source paper "learning to transfer texture from clothing images to 3d humans"):
  with members:
    - "the virtual tailor predicting clothing in 3d as a function of human pose shape and garment style"
    - "implicit functions in feature space for 3d shape reconstruction and completion"
    - "tex2shape detailed full human body geometry from a single image"
    - "unsupervised person image generation with semantic parsing transformation"
    - "learning to dress 3d people in generative clothing"
    - "learning to reconstruct people in clothing from a single rgb camera"
    - "360 degree textures of people in clothing from a single image"
    - "multi garment net learning to dress 3d people from images"

Connected through hyperedge HE-3 (induced by source paper "garmentgan photo realistic adversarial fashion transfer"):
  with members:
    - "unpaired pose guided human image generation"
    - "compatible and diverse fashion image inpainting"
    - "semantic image synthesis with spatially adaptive normalization"
    - "instance level human parsing via part grouping network"
    - "toward characteristic preserving image based virtual try on network"
    - "spectral normalization for generative adversarial networks"
    - "viton an image based virtual try on network"
    - "look into person self supervised structure sensitive learning and a new benchmark for human parsing"

Connected through hyperedge HE-4 (induced by source paper "sievenet a unified framework for robust image based virtual try on"):
  with members:
    - "context aware visual compatibility prediction"
    - "learning type aware embeddings for fashion compatibility"
    - "toward characteristic preserving image based virtual try on network"
    - "a variational u net for conditional appearance and shape generation"
    - "viton an image based virtual try on network"
    - "gans trained by a two time scale update rule converge to a nash equilibrium"
    - "deformable gans for pose based human image generation"
    - "improved techniques for training gans"

Connected through hyperedge HE-5 (induced by source paper "fashion minimal edits for outfit improvement"):
  with members:
    - "synthesizing images of humans in unseen poses"
    - "learning type aware embeddings for fashion compatibility"
    - "toward characteristic preserving image based virtual try on network"
    - "everybody dance now"
    - "viton an image based virtual try on network"
    - "texturegan controlling deep image synthesis with texture patches"
    - "creating capsule wardrobes from fashion images"
    - "streetstyle exploring world wide clothing styles from millions of photos"

Connected through hyperedge HE-6 (induced by source paper "fast video object segmentation with spatio temporal gans"):
  with members:
    - "video to video synthesis"
    - "learning to adapt structured output space for semantic segmentation"
    - "fast and accurate online video object segmentation via tracking parts"
    - "deep spatio temporal random fields for efficient video segmentation"
    - "efficient video object segmentation via network modulation"
    - "maskrnn instance level video object segmentation"
    - "videomatch matching based video object segmentation"
    - "large scale gan training for high fidelity natural image synthesis"

Connected through hyperedge HE-7 (induced by source paper "3dpeople modeling the geometry of dressed humans"):
  with members:
    - "wav2pix speech conditioned face generation using generative adversarial networks"
    - "bodynet volumetric inference of 3d human body shapes"
    - "talking face generation by adversarially disentangled audio visual representation"
    - "geometry aware network for non rigid shape prediction from a single view"
    - "adaptive o cnn a patch based deep representation of 3d shapes"
    - "3d human pose estimation in the wild by adversarial learning"
    - "siclope silhouette based clothed people"
    - "talking face generation by conditional recurrent adversarial network"

Connected through hyperedge HE-8 (induced by source paper "aggregation via separation boosting facial landmark detector with semi supervised style translation"):
  with members:
    - "look at boundary a boundary aware face alignment algorithm"
    - "synthesizing images of humans in unseen poses"
    - "disentangling 3d pose in a dendritic cnn for unconstrained 2d face alignment"
    - "wing loss for robust facial landmark localisation with convolutional neural networks"
    - "taskonomy disentangling task transfer learning"
    - "multimodal unsupervised image to image translation"
    - "style aggregated network for facial landmark detection"
    - "joint 3d face reconstruction and dense alignment with position map regression network"

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)