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: "identity preserving face completion for large ocular region occlusion"
  Abstract: We present a novel deep learning approach to synthesize complete face images in the presence of large ocular region occlusions. This is motivated by recent surge of VR/AR displays that hinder face-to-face communications. Different from the state-of-the-art face inpainting methods that have no control over the synthesized content and can only handle frontal face pose, our approach can faithfully recover the missing content under various head poses while preserving the identity. At the core of our method is a novel generative network with dedicated constraints to regularize the synthesis process. To preserve the identity, our network takes an arbitrary occlusion-free image of the target identity to infer the missing content, and its high-level CNN features as an identity prior to regularize the searching space of generator. Since the input reference image may have a different pose, a pose map and a novel pose discriminator are further adopted to supervise the learning of implicit pose transformations. Our method is capable of generating coherent facial inpainting with consistent identity over videos with large variations of head motions. Experiments on both synthesized and real data demonstrate that our method greatly outperforms the state-of-the-art methods in terms of both synthesis quality and robustness.

Connected through hyperedge HE-1 (induced by source paper "does generative face completion help face recognition"):
  with members:
    - "geometry aware face completion and editing"
    - "high resolution face completion with multiple controllable attributes via fully end to end progressive generative adversarial networks"
    - "free form image inpainting with gated convolution"
    - "additive margin softmax for face verification"
    - "learning deep models for face anti spoofing binary or auxiliary supervision"
    - "training deep networks with synthetic data bridging the reality gap by domain randomization"
    - "segmentation aware convolutional networks using local attention masks"
    - "vggface2 a dataset for recognising faces across pose and age"

Connected through hyperedge HE-2 (induced by source paper "boostgan for occlusive profile face frontalization and recognition"):
  with members:
    - "representation learning by rotating your faces"
    - "cosface large margin cosine loss for deep face recognition"
    - "load balanced gans for multi view face image synthesis"
    - "high resolution face completion with multiple controllable attributes via fully end to end progressive generative adversarial networks"
    - "spectral normalization for generative adversarial networks"
    - "sphereface deep hypersphere embedding for face recognition"
    - "beyond face rotation global and local perception gan for photorealistic and identity preserving frontal view synthesis"
    - "progressive growing of gans for improved quality stability and variation"

Connected through hyperedge HE-3 (induced by source paper "gif2video color dequantization and temporal interpolation of gif images"):
  with members:
    - "faceforensics a large scale video dataset for forgery detection in human faces"
    - "siclope silhouette based clothed people"
    - "video inpainting by jointly learning temporal structure and spatial details"
    - "super slomo high quality estimation of multiple intermediate frames for video interpolation"
    - "video frame interpolation via adaptive convolution"
    - "video frame interpolation via adaptive separable convolution"
    - "video frame synthesis using deep voxel flow"
    - "flownet 2 0 evolution of optical flow estimation with deep networks"

Connected through hyperedge HE-4 (induced by source paper "frame recurrent video inpainting by robust optical flow inference"):
  with members:
    - "gif2video color dequantization and temporal interpolation of gif images"
    - "learning blind video temporal consistency"
    - "faceforensics a large scale video dataset for forgery detection in human faces"
    - "deep temporal lstm for daily living action recognition"
    - "video inpainting by jointly learning temporal structure and spatial details"
    - "mganet a robust model for quality enhancement of compressed video"
    - "perceptual losses for real time style transfer and super resolution"
    - "semantic video segmentation by gated recurrent flow propagation"

Connected through hyperedge HE-5 (induced by source paper "frontal screens on head mounted displays to increase awareness of the hmd users state in mixed presence collaboration"):
  with members:
    - "eyemotion classifying facial expressions in vr using eye tracking cameras"
    - "facevr real time facial reenactment and eye gaze control in virtual reality"

Connected through hyperedge HE-6 (induced by source paper "on hallucinating context and background pixels from a face mask using multi scale gans"):
  with members:
    - "sc fegan face editing generative adversarial network with user s sketch and color"
    - "edgeconnect generative image inpainting with adversarial edge learning"
    - "faceshop deep sketch based face image editing"
    - "fast face image synthesis with minimal training"
    - "unified perceptual parsing for scene understanding"
    - "high resolution face completion with multiple controllable attributes via fully end to end progressive generative adversarial networks"
    - "the unreasonable effectiveness of deep features as a perceptual metric"
    - "a style based generator architecture for generative adversarial networks"

Connected through hyperedge HE-7 (induced by source paper "learning symmetry consistent deep cnns for face completion"):
  with members:
    - "the unreasonable effectiveness of deep features as a perceptual metric"
    - "learning warped guidance for blind face restoration"
    - "shift net image inpainting via deep feature rearrangement"
    - "generative image inpainting with contextual attention"
    - "vggface2 a dataset for recognising faces across pose and age"
    - "beyond face rotation global and local perception gan for photorealistic and identity preserving frontal view synthesis"
    - "generative face completion"
    - "contextual based image inpainting infer match and translate"

Connected through hyperedge HE-8 (induced by source paper "video inpainting by jointly learning temporal structure and spatial details"):
  with members:
    - "learning blind video temporal consistency"
    - "faceforensics a large scale video dataset for forgery detection in human faces"
    - "high resolution shape completion using deep neural networks for global structure and local geometry inference"
    - "can spatiotemporal 3d cnns retrace the history of 2d cnns and imagenet"
    - "shape inpainting using 3d generative adversarial network and recurrent convolutional networks"
    - "vconv dae deep volumetric shape learning without object labels"
    - "high resolution image inpainting using multi scale neural patch synthesis"
    - "shape completion enabled robotic grasping"

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)