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 "privacy preserving image based localization"):
  Abstract: Image-based localization is a core component of many augmented/mixed reality (AR/MR) and autonomous robotic systems. Current localization systems rely on the persistent storage of 3D point clouds of the scene to enable camera pose estimation, but such data reveals potentially sensitive scene information. This gives rise to significant privacy risks, especially as for many applications 3D mapping is a background process that the user might not be fully aware of. We pose the following question: How can we avoid disclosing confidential information about the captured 3D scene, and yet allow reliable camera pose estimation? This paper proposes the first solution to what we call privacy preserving image-based localization. The key idea of our approach is to lift the map representation from a 3D point cloud to a 3D line cloud. This novel representation obfuscates the underlying scene geometry while providing sufficient geometric constraints to enable robust and accurate 6-DOF camera pose estimation. Extensive experiments on several datasets and localization scenarios underline the high practical relevance of our proposed approach.

Includes members:
  Member "revealing scenes by inverting structure from motion reconstructions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "seeing the world in a bag of chips")
  Member "learning to anonymize faces for privacy preserving action detection":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "deep poisoning functions towards robust privacy safe image data sharing")
  Member "semantic visual localization":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "segmap segment based mapping and localization using data driven descriptors")
  Member "privacy preserving visual learning using doubly permuted homomorphic encryption":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "mechanism design for multi party machine learning")
  Member "segmatch segment based place recognition in 3d point clouds":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "segmap segment based mapping and localization using data driven descriptors")
  Member "privacy preserving human activity recognition from extreme low resolution":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "an adversarial learning framework for preserving users anonymity in face based emotion recognition")
  Member "planet photo geolocation with convolutional neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "mvp unified motion and visual self supervised learning for large scale robotic navigation")
  Member "dsac differentiable ransac for camera localization":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "visual camera re localization from rgb and rgb d images using dsac")

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)