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 "temporally coherent general dynamic scene reconstruction"):
  Abstract: Existing techniques for dynamic scene reconstruction from multiple wide-baseline cameras primarily focus on reconstruction in controlled environments, with fixed calibrated cameras and strong prior constraints. This paper introduces a general approach to obtain a 4D representation of complex dynamic scenes from multi-view wide-baseline static or moving cameras without prior knowledge of the scene structure, appearance, or illumination. Contributions of the work are: An automatic method for initial coarse reconstruction to initialize joint estimation; Sparse-to-dense temporal correspondence integrated with joint multi-view segmentation and reconstruction to introduce temporal coherence; and a general robust approach for joint segmentation refinement and dense reconstruction of dynamic scenes by introducing shape constraint. Comparison with state-of-the-art approaches on a variety of complex indoor and outdoor scenes, demonstrates improved accuracy in both multi-view segmentation and dense reconstruction. This paper demonstrates unsupervised reconstruction of complete temporally coherent 4D scene models with improved non-rigid object segmentation and shape reconstruction and its application to free-viewpoint rendering and virtual reality.

Includes members:
  Member "veritatem dies aperit temporally consistent depth prediction enabled by a multi task geometric and semantic scene understanding approach":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "to complete or to estimate that is the question a multi task approach to depth completion and monocular depth estimation")
  Member "learning 3d shape completion under weak supervision":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "multimodal shape completion via conditional generative adversarial networks")
  Member "specular to diffuse translation for multi view reconstruction":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "mini unmanned aerial vehicle based remote sensing techniques applications and prospects")
  Member "temporally coherent 4d reconstruction of complex dynamic scenes":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "u4d unsupervised 4d dynamic scene understanding")
  Member "flow fields dense correspondence fields for highly accurate large displacement optical flow estimation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "learning depth via interaction")
  Member "coherent motion segmentation in moving camera videos using optical flow orientations":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "moving objects detection with a moving camera a comprehensive review")

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)