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 "visual localization under appearance change a filtering approach"):
  Abstract: A major focus of current research on place recognition is visual localization for autonomous driving, which must be robust against significant appearance change. This work makes three contributions towards solving visual localization under appearance change: i) We present G2D, a software that enables capturing videos from Grand Theft Auto V, a popular role playing game set in an expansive virtual city. The target users of our software are robotic vision researchers who wish to collect hyper-realistic computer-generated imagery of a city from the street level, under controlled 6 DoF camera poses and different environmental conditions; ii) Using G2D, we construct a synthetic dataset simulating a realistic setting, i.e., multiple vehicles traversing through a road network in an urban area under different environmental conditions; iii) Based on image retrieval using local features and an encoding technique, a novel Monte Carlo localization algorithm is proposed. The experimental results show that our proposed method achieves better results than state-of-the-art approaches for the task on visual localization under significant appearance change. The dataset will be available online upon acceptance. G2D is made available at: this https URL

Includes members:
  Member "on device scalable image based localization via prioritized cascade search and fast one many ransac":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "simultaneous feature aggregating and hashing for compact binary code learning")
  Member "g2d from gta to data":
    also connected through other hyperedges:
      (none)
  Member "training deep networks with synthetic data bridging the reality gap by domain randomization":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "increasing generality in machine learning through procedural content generation")
  Member "geometric loss functions for camera pose regression with deep learning":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "neural mesh refiner for 6 dof pose estimation")
  Member "semantic visual localization":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "segmap segment based mapping and localization using data driven descriptors")
  Member "geometry aware learning of maps for camera localization":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "pointloc deep pose regressor for lidar point cloud localization")
  Member "playing for benchmarks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "virtual kitti 2")
  Member "image based localization using lstms for structured feature correlation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "pointloc deep pose regressor for lidar point cloud 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)