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: "salsa a novel dataset for multimodal group behavior analysis"
  Abstract: Studying free-standing conversational groups (FCGs) in unstructured social settings (e.g., cocktail party ) is gratifying due to the wealth of information available at the group (mining social networks) and individual (recognizing native behavioral and personality traits) levels. However, analyzing social scenes involving FCGs is also highly challenging due to the difficulty in extracting behavioral cues such as target locations, their speaking activity and head/body pose due to crowdedness and presence of extreme occlusions. To this end, we propose SALSA, a novel dataset facilitating multimodal and Synergetic sociAL Scene Analysis, and make two main contributions to research on automated social interaction analysis: (1) SALSA records social interactions among 18 participants in a natural, indoor environment for over 60 minutes, under the poster presentation and cocktail party contexts presenting difficulties in the form of low-resolution images, lighting variations, numerous occlusions, reverberations and interfering sound sources; (2) To alleviate these problems we facilitate multimodal analysis by recording the social interplay using four static surveillance cameras and sociometric badges worn by each participant, comprising the microphone, accelerometer, bluetooth and infrared sensors. In addition to raw data, we also provide annotations concerning individuals' personality as well as their position, head, body orientation and F-formation information over the entire event duration. Through extensive experiments with state-of-the-art approaches, we show (a) the limitations of current methods and (b) how the recorded multiple cues synergetically aid automatic analysis of social interactions. SALSA is available at this http URL

Connected through hyperedge HE-1 (induced by source paper "panda a gigapixel level human centric video dataset"):
  with members:
    - "eurocity persons a novel benchmark for person detection in traffic scenes"
    - "cvpr19 tracking and detection challenge how crowded can it get"
    - "collaborative global local networks for memory efficient segmentation of ultra high resolution images"
    - "widerperson a diverse dataset for dense pedestrian detection in the wild"
    - "group reidentification with multigrained matching and integration"
    - "mmdetection open mmlab detection toolbox and benchmark"
    - "vision meets drones a challenge"
    - "traphic trajectory prediction in dense and heterogeneous traffic using weighted interactions"

Connected through hyperedge HE-2 (induced by source paper "a bayesian filter for multi view 3d multi object tracking with occlusion handling"):
  with members:
    - "deep multi camera people detection"
    - "deep occlusion reasoning for multi camera multi target detection"
    - "yolo9000 better faster stronger"
    - "performance measures and a data set for multi target multi camera tracking"
    - "you only look once unified real time object detection"
    - "fast r cnn"
    - "high speed tracking with kernelized correlation filters"
    - "motchallenge 2015 towards a benchmark for multi target tracking"

Connected through hyperedge HE-3 (induced by source paper "a bayesian 3d multi view multi object tracking filter"):
  with members:
    - "deep multi camera people detection"
    - "deep occlusion reasoning for multi camera multi target detection"
    - "yolo9000 better faster stronger"
    - "performance measures and a data set for multi target multi camera tracking"
    - "fast r cnn"
    - "motchallenge 2015 towards a benchmark for multi target tracking"

Connected through hyperedge HE-4 (induced by source paper "improving social awareness through dante a deep affinity network for clustering conversational interactants"):
  with members:
    - "deep local trajectory replanning and control for robot navigation"
    - "towards social artificial intelligence nonverbal social signal prediction in a triadic interaction"
    - "openpose realtime multi person 2d pose estimation using part affinity fields"
    - "social gan socially acceptable trajectories with generative adversarial networks"
    - "conversational group detection with deep convolutional networks"
    - "adam a method for stochastic optimization"

Connected through hyperedge HE-5 (induced by source paper "audio visual embodied navigation"):
  with members:
    - "two body problem collaborative visual task completion"
    - "embodied question answering in photorealistic environments with point cloud perception"
    - "do autonomous agents benefit from hearing"
    - "the replica dataset a digital replica of indoor spaces"
    - "benchmarking classic and learned navigation in complex 3d environments"
    - "co separating sounds of visual objects"
    - "splitnet sim2sim and task2task transfer for embodied visual navigation"
    - "interactive gibson benchmark for interactive navigation in cluttered environments"

Connected through hyperedge HE-6 (induced by source paper "towards social artificial intelligence nonverbal social signal prediction in a triadic interaction"):
  with members:
    - "on the convergence of adam and beyond"
    - "total capture a 3d deformation model for tracking faces hands and bodies"
    - "social gan socially acceptable trajectories with generative adversarial networks"
    - "learning to generate long term future via hierarchical prediction"
    - "towards 3d human pose estimation in the wild a weakly supervised approach"
    - "recent trends in deep learning based natural language processing"
    - "a simple yet effective baseline for 3d human pose estimation"
    - "hand keypoint detection in single images using multiview bootstrapping"

Connected through hyperedge HE-7 (induced by source paper "being the center of attention a person context cnn framework for personality recognition"):
  with members:
    - "structural recurrent neural network srnn for group activity analysis"
    - "persemon a deep network for joint analysis of apparent personality emotion and their relationship"
    - "rgb d based human motion recognition with deep learning a survey"
    - "a new representation of skeleton sequences for 3d action recognition"
    - "skepxels spatio temporal image representation of human skeleton joints for action recognition"
    - "social scene understanding end to end multi person action localization and collective activity recognition"
    - "realtime multi person 2d pose estimation using part affinity fields"
    - "learning deep features for discriminative localization"

Connected through hyperedge HE-8 (induced by source paper "visual social relationship recognition"):
  with members:
    - "towards a visual privacy advisor understanding and predicting privacy risks in images"
    - "deep label distribution learning with label ambiguity"
    - "don t just assume look and answer overcoming priors for visual question answering"
    - "focal loss for dense object detection"
    - "a domain based approach to social relation recognition"
    - "speaking the same language matching machine to human captions by adversarial training"
    - "moviegraphs towards understanding human centric situations from videos"
    - "dual glance model for deciphering social relationships"

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)