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 "the direction aware learnable additive kernels and the adversarial network for deep floor plan recognition"):
  Abstract: This paper presents a new approach for the recognition of elements in floor plan layouts. Besides of elements with common shapes, we aim to recognize elements with irregular shapes such as circular rooms and inclined walls. Furthermore, the reduction of noise in the semantic segmentation of the floor plan is on demand. To this end, we propose direction-aware, learnable, additive kernels in the application of both the context module and common convolutional blocks. We apply them for high performance of elements with both common and irregular shapes. Besides, an adversarial network with two discriminators is proposed to further improve the accuracy of the elements and to reduce the noise of the semantic segmentation. Experimental results demonstrate the superiority and effectiveness of the proposed network over the state-of-the-art methods.

Includes members:
  Member "deep floor plan recognition using a multi task network with room boundary guided attention":
    also connected through other hyperedges:
      (none)
  Member "horizonnet learning room layout with 1d representation and pano stretch data augmentation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "coco gan generation by parts via conditional coordinating")
  Member "acnet strengthening the kernel skeletons for powerful cnn via asymmetric convolution blocks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "correlated initialization for correlated data")
  Member "layoutnet reconstructing the 3d room layout from a single rgb image":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "scan2plan efficient floorplan generation from 3d scans of indoor scenes")
  Member "dula net a dual projection network for estimating room layouts from a single rgb panorama":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "structured3d a large photo realistic dataset for structured 3d modeling")
  Member "encoder decoder with atrous separable convolution for semantic image segmentation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "learning enriched features for real image restoration and enhancement")
  Member "cycada cycle consistent adversarial domain adaptation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a novel framework for selection of gans for an application")
  Member "a fast rcnn hard positive generation via adversary for object detection":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "on leveraging pretrained gans for limited data generation")

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)