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: "face expression recognition and analysis the state of the art"
  Abstract: The automatic recognition of facial expressions has been an active research topic since the early nineties. There have been several advances in the past few years in terms of face detection and tracking, feature extraction mechanisms and the techniques used for expression classification. This paper surveys some of the published work since 2001 till date. The paper presents a time-line view of the advances made in this field, the applications of automatic face expression recognizers, the characteristics of an ideal system, the databases that have been used and the advances made in terms of their standardization and a detailed summary of the state of the art. The paper also discusses facial parameterization using FACS Action Units (AUs) and MPEG-4 Facial Animation Parameters (FAPs) and the recent advances in face detection, tracking and feature extraction methods. Notes have also been presented on emotions, expressions and facial features, discussion on the six prototypic expressions and the recent studies on expression classifiers. The paper ends with a note on the challenges and the future work. This paper has been written in a tutorial style with the intention of helping students and researchers who are new to this field.

Connected through hyperedge HE-1 (induced by source paper "dual attention mobdensenet damdnet for robust 3d face alignment"):
  with members:
    - "wing loss for robust facial landmark localisation with convolutional neural networks"
    - "joint 3d face reconstruction and dense alignment with position map regression network"
    - "nonlinear 3d face morphable model"
    - "mobilenets efficient convolutional neural networks for mobile vision applications"
    - "squeeze and excitation networks"
    - "aggregated residual transformations for deep neural networks"
    - "densely connected convolutional networks"
    - "regressing robust and discriminative 3d morphable models with a very deep neural network"

Connected through hyperedge HE-2 (induced by source paper "face alignment in full pose range a 3d total solution"):
  with members:
    - "pose invariant face alignment with a single cnn"
    - "finding tiny faces"
    - "unconstrained facial landmark localization with backbone branches fully convolutional networks"
    - "facial landmark detection with tweaked convolutional neural networks"
    - "human pose estimation with iterative error feedback"
    - "pose invariant 3d face alignment"
    - "effective face frontalization in unconstrained images"
    - "going deeper with convolutions"

Connected through hyperedge HE-3 (induced by source paper "a survey of automatic facial micro expression analysis databases methods and challenges"):
  with members:
    - "enriched long term recurrent convolutional network for facial micro expression recognition"
    - "less is more micro expression recognition from video using apex frame"
    - "towards reading hidden emotions a comparative study of spontaneous micro expression spotting and recognition methods"
    - "objective classes for micro facial expression recognition"
    - "sparsity in dynamics of spontaneous subtle emotions analysis and application"
    - "learning a target sample re generator for cross database micro expression recognition"
    - "spontaneous subtle expression detection and recognition based on facial strain"
    - "objective micro facial movement detection using facs based regions and baseline evaluation"

Connected through hyperedge HE-4 (induced by source paper "facial expression analysis under partial occlusion a survey"):
  with members:
    - "towards reading hidden emotions a comparative study of spontaneous micro expression spotting and recognition methods"
    - "emotionet challenge recognition of facial expressions of emotion in the wild"
    - "fera 2017 addressing head pose in the third facial expression recognition and analysis challenge"
    - "avec 2016 depression mood and emotion recognition workshop and challenge"
    - "confidence weighted local expression predictions for occlusion handling in expression recognition and action unit detection"

Connected through hyperedge HE-5 (induced by source paper "alzheimer s disease diagnosis based on cognitive methods in virtual environments and emotions analysis"):
  with members:
    - "fera 2017 addressing head pose in the third facial expression recognition and analysis challenge"
    - "facenet2expnet regularizing a deep face recognition net for expression recognition"
    - "modeling spatial and temporal cues for multi label facial action unit detection"
    - "identifying stable patterns over time for emotion recognition from eeg"

Connected through hyperedge HE-6 (induced by source paper "features extraction based on an origami representation of 3d landmarks"):
  with members:
    - "spatial temporal graph convolutional networks for skeleton based action recognition"
    - "disentangling 3d pose in a dendritic cnn for unconstrained 2d face alignment"
    - "skeleton based relational modeling for action recognition"
    - "fera 2017 addressing head pose in the third facial expression recognition and analysis challenge"

Connected through hyperedge HE-7 (induced by source paper "joint multi view face alignment in the wild"):
  with members:
    - "a comprehensive performance evaluation of deformable face tracking in the wild"
    - "densereg fully convolutional dense shape regression in the wild"
    - "arcface additive angular margin loss for deep face recognition"
    - "face detection using deep learning an improved faster rcnn approach"
    - "uv gan adversarial facial uv map completion for pose invariant face recognition"
    - "binarized convolutional landmark localizers for human pose estimation and face alignment with limited resources"
    - "robust facial landmark detection under significant head poses and occlusion"
    - "stacked hourglass networks for human pose estimation"

Connected through hyperedge HE-8 (induced by source paper "eyemotion classifying facial expressions in vr using eye tracking cameras"):
  with members:
    - "mask off synthesizing face images in the presence of head mounted displays"
    - "eye tracking for everyone"
    - "training deep networks for facial expression recognition with crowd sourced label distribution"
    - "the nd iris 0405 iris image dataset"
    - "facevr real time facial reenactment and eye gaze control in virtual reality"
    - "peak piloted deep network for facial expression recognition"
    - "tensorflow large scale machine learning on heterogeneous distributed systems"
    - "facenet a unified embedding for face recognition and clustering"

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)