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 "video compressive sensing for spatial multiplexing cameras using motion flow models"):
  Abstract: Spatial multiplexing cameras (SMCs) acquire a (typically static) scene through a series of coded projections using a spatial light modulator (e.g., a digital micro-mirror device) and a few optical sensors. This approach finds use in imaging applications where full-frame sensors are either too expensive (e.g., for short-wave infrared wavelengths) or unavailable. Existing SMC systems reconstruct static scenes using techniques from compressive sensing (CS). For videos, however, existing acquisition and recovery methods deliver poor quality. In this paper, we propose the CS multi-scale video (CS-MUVI) sensing and recovery framework for high-quality video acquisition and recovery using SMCs. Our framework features novel sensing matrices that enable the efficient computation of a low-resolution video preview, while enabling high-resolution video recovery using convex optimization. To further improve the quality of the reconstructed videos, we extract optical-flow estimates from the low-resolution previews and impose them as constraints in the recovery procedure. We demonstrate the efficacy of our CS-MUVI framework for a host of synthetic and real measured SMC video data, and we show that high-quality videos can be recovered at roughly $60\times$ compression.

Includes members:
  Member "lisens a scalable architecture for video compressive sensing":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "targeted nonlinear adversarial perturbations in images and videos")
  Member "fpa cs focal plane array based compressive imaging in short wave infrared":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "solving inverse computational imaging problems using deep pixel level prior")
  Member "compressive coded aperture keyed exposure imaging with optical flow reconstruction":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "fpa cs focal plane array based compressive imaging in short wave infrared")
  Member "coded aperture compressive temporal imaging":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "event driven video frame synthesis")
  Member "the stone transform multi resolution image enhancement and real time compressive video":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "multi resolution compressive sensing reconstruction")
  Member "compressive acquisition of dynamic scenes":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "privacy preserving action recognition using coded aperture videos")

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)