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 "flowfusion dynamic dense rgb d slam based on optical flow"):
  Abstract: Dynamic environments are challenging for visual SLAM since the moving objects occlude the static environment features and lead to wrong camera motion estimation. In this paper, we present a novel dense RGB-D SLAM solution that simultaneously accomplishes the dynamic/static segmentation and camera ego-motion estimation as well as the static background reconstructions. Our novelty is using optical flow residuals to highlight the dynamic semantics in the RGB-D point clouds and provide more accurate and efficient dynamic/static segmentation for camera tracking and background reconstruction. The dense reconstruction results on public datasets and real dynamic scenes indicate that the proposed approach achieved accurate and efficient performances in both dynamic and static environments compared to state-of-the-art approaches.

Includes members:
  Member "learning rigidity in dynamic scenes with a moving camera for 3d motion field estimation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "sense a shared encoder network for scene flow estimation")
  Member "ds slam a semantic visual slam towards dynamic environments":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "perception and decision making of autonomous systems in the era of learning an overview")
  Member "mid fusion octree based object level multi instance dynamic slam":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "3d dynamic scene graphs actionable spatial perception with places objects and humans")
  Member "co fusion real time segmentation tracking and fusion of multiple objects":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "3d dynamic scene graphs actionable spatial perception with places objects and humans")
  Member "optical flow in mostly rigid scenes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "joint unsupervised learning of optical flow and egomotion with bi level optimization")
  Member "orb slam2 an open source slam system for monocular stereo and rgb d cameras":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "perception and decision making of autonomous systems in the era of learning an overview")
  Member "pwc net cnns for optical flow using pyramid warping and cost volume":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "probabilistic future prediction for video scene understanding")
  Member "learning to refine object segments":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "stem seg spatio temporal embeddings for instance segmentation in videos")

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.RO(Robotics)