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 "multi view stereo 3d edge reconstruction"):
  Abstract: This paper presents a novel method for the reconstruction of 3D edges in multi-view stereo scenarios. Previous research in the field typically relied on video sequences and limited the reconstruction process to either straight line-segments, or edge-points, i.e., 3D points that correspond to image edges. We instead propose a system, denoted as EdgeGraph3D, able to recover both straight and curved 3D edges from an unordered image sequence. A second contribution of this work is a graph-based representation for 2D edges that allows the identification of the most structurally significant edges detected in an image. We integrate EdgeGraph3D in a multi-view stereo reconstruction pipeline and analyze the benefits provided by 3D edges to the accuracy of the recovered surfaces. We evaluate the effectiveness of our approach on multiple datasets from two different collections in the multi-view stereo literature. Experimental results demonstrate the ability of EdgeGraph3D to work in presence of strong illumination changes and reflections, which are usually detrimental to the effectiveness of classical photometric reconstruction systems.

Includes members:
  Member "detail preserving and content aware variational multi view stereo reconstruction":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "mesh based camera pairs selection and occlusion aware masking for mesh refinement")
  Member "incremental reconstruction of urban environments by edge points delaunay triangulation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "creating navigable space from sparse noisy map points")

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)