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 "aesthetic quality assessment for group photograph"):
  Abstract: Image aesthetic quality assessment has got much attention in recent years, but not many works have been done on a specific genre of photos: Group photograph. In this work, we designed a set of high-level features based on the experience and principles of group photography: Opened-eye, Gaze, Smile, Occluded faces, Face Orientation, Facial blur, Character center. Then we combined them and 83 generic aesthetic features to build two aesthetic assessment models. We also constructed a large dataset of group photographs - GPD- annotated with the aesthetic score. The experimental result shows that our features perform well for categorizing professional photos and snapshots and predicting the distinction of multiple group photographs of diverse human states under the same scene.

Includes members:
  Member "an universal image attractiveness ranking framework":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "watermark signal detection and its application in image retrieval")
  Member "nima neural image assessment":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "active fine tuning from gmad examples improves blind image quality assessment")
  Member "ilgnet inception modules with connected local and global features for efficient image aesthetic quality classification using domain adaptation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "image aesthetics assessment using composite features from off the shelf deep models")
  Member "photo aesthetics ranking network with attributes and content adaptation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "composition aware image aesthetics assessment")
  Member "will people like your image learning the aesthetic space":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "composition aware image aesthetics assessment")
  Member "the beauty of capturing faces rating the quality of digital portraits":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "beholder gan generation and beautification of facial images with conditioning on their beauty level")

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)