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 "jrmot a real time 3d multi object tracker and a new large scale dataset"):
  Abstract: An autonomous navigating agent needs to perceive and track the motion of objects and other agents in its surroundings to achieve robust and safe motion planning and execution. While autonomous navigation requires a multi-object tracking (MOT) system to provide 3D information, most research has been done in 2D MOT from RGB videos. In this work we present JRMOT, a novel 3D MOT system that integrates information from 2D RGB images and 3D point clouds into a real-time performing framework. Our system leverages advancements in neural-network based re-identification as well as 2D and 3D detection and descriptors. We incorporate this into a joint probabilistic data-association framework within a multi-modal recursive Kalman architecture to achieve online, real-time 3D MOT. As part of our work, we release the JRDB dataset, a novel large scale 2D+3D dataset and benchmark annotated with over 2 million boxes and 3500 time consistent 2D+3D trajectories across 54 indoor and outdoor scenes. The dataset contains over 60 minutes of data including 360 degree cylindrical RGB video and 3D pointclouds. The presented 3D MOT system demonstrates state-of-the-art performance against competing methods on the popular 2D tracking KITTI benchmark and serves as a competitive 3D tracking baseline for our dataset and benchmark.

Includes members:
  Member "a baseline for 3d multi object tracking":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "sequential forecasting of 100 000 points")
  Member "tracking without bells and whistles":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "multiple object tracking by flowing and fusing")
  Member "track to reconstruct and reconstruct to track":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "dymslam 4d dynamic scene reconstruction based on geometrical motion segmentation")
  Member "nuscenes a multimodal dataset for autonomous driving":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "review deep learning on 3d point clouds")
  Member "fantrack 3d multi object tracking with feature association network":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "joint 3d tracking and forecasting with graph neural network and diversity sampling")
  Member "online multiple pedestrian tracking using deep temporal appearance matching association":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "occlusion robust online multi object visual tracking using a gm phd filter with a cnn based re identification")
  Member "multi object tracking with multiple cues and switcher aware classification":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "multiple object tracking by flowing and fusing")
  Member "beyond pixels leveraging geometry and shape cues for online multi object tracking":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "multimodal end to end autonomous driving")

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)