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: "mvor a multi view rgb d operating room dataset for 2d and 3d human pose estimation"
  Abstract: Person detection and pose estimation is a key requirement to develop intelligent context-aware assistance systems. To foster the development of human pose estimation methods and their applications in the Operating Room (OR), we release the Multi-View Operating Room (MVOR) dataset, the first public dataset recorded during real clinical interventions. It consists of 732 synchronized multi-view frames recorded by three RGB-D cameras in a hybrid OR. It also includes the visual challenges present in such environments, such as occlusions and clutter. We provide camera calibration parameters, color and depth frames, human bounding boxes, and 2D/3D pose annotations. In this paper, we present the dataset, its annotations, as well as baseline results from several recent person detection and 2D/3D pose estimation methods. Since we need to blur some parts of the images to hide identity and nudity in the released dataset, we also present a comparative study of how the baselines have been impacted by the blurring. Results show a large margin for improvement and suggest that the MVOR dataset can be useful to compare the performance of the different methods.

Connected through hyperedge HE-1 (induced by source paper "metric scale truncation robust heatmaps for 3d human pose estimation"):
  with members:
    - "in the wild human pose estimation using explicit 2d features and intermediate 3d representations"
    - "ordinal depth supervision for 3d human pose estimation"
    - "multi scale structure aware network for human pose estimation"
    - "yolov3 an incremental improvement"
    - "video based reconstruction of 3d people models"
    - "2d 3d pose estimation and action recognition using multitask deep learning"
    - "how robust is 3d human pose estimation to occlusion"
    - "3d human pose estimation in the wild by adversarial learning"

Connected through hyperedge HE-2 (induced by source paper "face detection in the operating room comparison of state of the art methods and a self supervised approach"):
  with members:
    - "simple baselines for human pose estimation and tracking"
    - "faceoff anonymizing videos in the operating rooms"
    - "s 3 fd single shot scale invariant face detector"
    - "data distillation towards omni supervised learning"
    - "surgical data science for next generation interventions"
    - "articulated clinician detection using 3d pictorial structures on rgb d data"
    - "ssh single stage headless face detector"
    - "cascaded pyramid network for multi person pose estimation"

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)