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 "natural and effective obfuscation by head inpainting"):
  Abstract: As more and more personal photos are shared online, being able to obfuscate identities in such photos is becoming a necessity for privacy protection. People have largely resorted to blacking out or blurring head regions, but they result in poor user experience while being surprisingly ineffective against state of the art person recognizers. In this work, we propose a novel head inpainting obfuscation technique. Generating a realistic head inpainting in social media photos is challenging because subjects appear in diverse activities and head orientations. We thus split the task into two sub-tasks: (1) facial landmark generation from image context (e.g. body pose) for seamless hypothesis of sensible head pose, and (2) facial landmark conditioned head inpainting. We verify that our inpainting method generates realistic person images, while achieving superior obfuscation performance against automatic person recognizers.

Includes members:
  Member "person recognition in personal photo collections":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "shape evasion preventing body shape inference of multi stage approaches")
  Member "gp gan gender preserving gan for synthesizing faces from landmarks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "multi channel attention selection gans for guided image to image translation")
  Member "recent progress of face image synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "privacynet semi adversarial networks for multi attribute face privacy")
  Member "pose guided person image generation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "chained representation cycling learning to estimate 3d human pose and shape by cycling between representations")
  Member "a domain based approach to social relation recognition":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "meta transfer learning through hard tasks")
  Member "segan segmenting and generating the invisible":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "the impact of hole geometry on relative robustness of in painting networks an empirical study")
  Member "adversarial image perturbation for privacy protection a game theory perspective":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "dynamic backdoor attacks against machine learning models")
  Member "synthesizing normalized faces from facial identity features":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "vec2face unveil human faces from their blackbox features in face recognition")

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)