human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "using panoramic videos for multi person localization and tracking in a 3d panoramic coordinate"):
  Abstract: This work proposes a new human-related video processing task named 3D panoramic multi-person localization and tracking. With a benchmark dataset and a simple yet effective solution, it establishes a new paradigm for multi-person tracking systems and related applications. Unlike existing methods that can only work on a 2D coordinate or a narrow-angle-view 3D coordinate, our proposal can maximally explore the 3D trajectory information of tracking targets. This is approached by applying camera geometry to transform human locations from 2D panoramic image coordinates to a 3D panoramic camera coordinate, and then by applying a tracking algorithm that associates human appearance and 3D trajectory together.

Includes members:
  Member "pifpaf composite fields for human pose estimation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "higherhrnet scale aware representation learning for bottom up human pose estimation")
  Member "moana an online learned adaptive appearance model for robust multiple object tracking in 3d":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "rodnet object detection under severe conditions using vision radio cross modal supervision")
  Member "monoloco monocular 3d pedestrian localization and uncertainty estimation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "monopair monocular 3d object detection using pairwise spatial relationships")
  Member "bag of tricks and a strong baseline for deep person re identification":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "building computationally efficient and well generalizing person re identification models with metric learning")
  Member "beyond pixels leveraging geometry and shape cues for online multi object tracking":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "jrmot a real time 3d multi object tracker and a new large scale dataset")
  Member "combined image and world space tracking in traffic scenes":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "joint 3d tracking and forecasting with graph neural network and diversity sampling")
  Member "mono camera 3d multi object tracking using deep learning detections and pmbm filtering":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "jrmot a real time 3d multi object tracker and a new large scale dataset")
  Member "structured attention guided convolutional neural fields for monocular depth estimation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "mti net multi scale task interaction networks for multi task learning")

Question: Please tell me which class the source paper 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)