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 "robot to robot relative pose estimation using humans as markers"):
  Abstract: In this paper, we propose a method to determine the 3D relative pose of pairs of communicating robots by using human pose-based key-points as correspondences. We adopt a `leader-follower' framework where the leader robot detects and triangulates the key-points in its own frame of reference. Afterwards, the follower robots match the corresponding 2D projections on their respective calibrated cameras and find their relative poses by solving the perspective-n-point (PnP) problem. In the proposed method, we use the state-of-the-art pose detector named OpenPose for extracting the pose-based key-points pertaining to humans in the scene. Additionally, we design an efficient model for person re-identification and present an iterative optimization algorithm to refine the key-point correspondences based on their local structural similarities in the image space. We evaluate the performance of the proposed relative pose estimation method through a number of experiments conducted in terrestrial and underwater environments. Finally, we discuss the relevant operational challenges of this approach and analyze its feasibility for multi-robot cooperative systems in human-dominated social settings and in feature-deprived environments such as underwater.

Includes members:
  Member "underwater surveying via bearing only cooperative localization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "machine vision for improved human robot cooperation in adverse underwater conditions")
  Member "person following by autonomous robots a categorical overview":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "machine vision for improved human robot cooperation in adverse underwater conditions")
  Member "densepose dense human pose estimation in the wild":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "neural human video rendering joint learning of dynamic textures and rendering to video translation")
  Member "realtime multi person 2d pose estimation using part affinity fields":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "posenet3d unsupervised 3d human shape and pose estimation")
  Member "deepcut joint subset partition and labeling for multi person pose estimation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "neural human video rendering joint learning of dynamic textures and rendering to video translation")
  Member "deeppose human pose estimation via deep neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "metric scale truncation robust heatmaps for 3d human pose estimation")
  Member "exact global histogram specification optimized for structural similarity":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "learning to respond with stickers a framework of unifying multi modality in multi turn dialog")

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)