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 "you are here geolocation by embedding maps and images"):
  Abstract: We present a novel approach to geolocating images on a 2-D map based on learning a low dimensional embedded space, which allows a comparison between an image captured at a location and local neighbourhoods of the map. The representation is not sufficiently discriminatory to allow localisation from a single image but when concatenated along a route, localisation converges quickly, with over 90% accuracy being achieved for routes up to 200m in length when using Google Street View and Open Street Map data. The approach generalises a previous fixed semantic feature based approach and achieves faster convergence and higher accuracy without the need for including turn information.

Includes members:
  Member "towards navigation without precise localization weakly supervised learning of goal directed navigation cost map":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "mvp unified motion and visual self supervised learning for large scale robotic navigation")
  Member "variational end to end navigation and localization":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "probabilistic future prediction for video scene understanding")
  Member "automated map reading image based localisation in 2 d maps using binary semantic descriptors":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "end to end learning of driving models with surround view cameras and route planners")
  Member "in defense of the triplet loss for person re identification":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "stem seg spatio temporal embeddings for instance segmentation in videos")
  Member "learning from maps visual common sense for autonomous driving":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "learning a layout transfer network for context aware object detection")
  Member "find your way by observing the sun and other semantic cues":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "shadow transfer single image relighting for urban road scenes")
  Member "localizing and orienting street views using overhead imagery":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "multi channel attention selection gans for guided image to image translation")
  Member "semantic image based geolocation given a map":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "lending orientation to neural networks for cross view geo localization")

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)