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 modal non line of sight passive imaging"):
  Abstract: We consider the non-line-of-sight (NLOS) imaging of an object using light reflected off a diffusive wall. The wall scatters incident light such that a lens is no longer useful to form an image. Instead, we exploit the four-dimensional spatial coherence function to reconstruct a two-dimensional projection of the obscured object. The approach is completely passive in the sense that no control over the light illuminating the object is assumed, and is compatible with the partially coherent fields ubiquitous in both indoor and outdoor environments. We formulate a multi-criteria convex optimization problem for reconstruction, which fuses reflected field's intensity and spatial coherence information at different scales. Our formulation leverages established optics models of light propagation and scattering and exploits the sparsity common to many images in different bases. We also develop an algorithm based on the Alternating Direction Method of Multipliers to efficiently solve the convex program proposed. A means for analyzing the null space of the measurement matrices is provided, as well as a means for weighing the contribution of individual measurements to the reconstruction. This work holds promise to advance passive imaging in challenging NLOS regimes in which the intensity does not necessarily retain distinguishable features, and provides a framework for multi-modal information fusion for efficient scene reconstruction.

Includes members:
  Member "joint defogging and demosaicking":
    also connected through other hyperedges:
      (none)
  Member "optically lightweight tracking of objects around a corner":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "deep non line of sight reconstruction")

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)