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 "casia surf cefa a benchmark for multi modal cross ethnicity face anti spoofing"):
  Abstract: Ethnic bias has proven to negatively affect the performance of face recognition systems, and it remains an open research problem in face anti-spoofing. In order to study the ethnic bias for face anti-spoofing, we introduce the largest up to date CASIA-SURF Cross-ethnicity Face Anti-spoofing (CeFA) dataset (briefly named CeFA), covering $3$ ethnicities, $3$ modalities, $1,607$ subjects, and 2D plus 3D attack types. Four protocols are introduced to measure the affect under varied evaluation conditions, such as cross-ethnicity, unknown spoofs or both of them. To the best of our knowledge, CeFA is the first dataset including explicit ethnic labels in current published/released datasets for face anti-spoofing. Then, we propose a novel multi-modal fusion method as a strong baseline to alleviate these bias, namely, the static-dynamic fusion mechanism applied in each modality (i.e., RGB, Depth and infrared image). Later, a partially shared fusion strategy is proposed to learn complementary information from multiple modalities. Extensive experiments demonstrate that the proposed method achieves state-of-the-art results on the CASIA-SURF, OULU-NPU, SiW and the CeFA dataset.

Includes members:
  Member "casia surf a large scale multi modal benchmark for face anti spoofing":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "static and dynamic fusion for multi modal cross ethnicity face anti spoofing")
  Member "face alignment in full pose range a 3d total solution":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "rotate and render unsupervised photorealistic face rotation from single view images")
  Member "face de spoofing anti spoofing via noise modeling":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "deep frequent spatial temporal learning for face anti spoofing")
  Member "exploiting temporal and depth information for multi frame face anti spoofing":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "searching central difference convolutional networks for face anti spoofing")
  Member "a dataset and benchmark for large scale multi modal face anti spoofing":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "deep frequent spatial temporal learning for face anti spoofing")
  Member "joint 3d face reconstruction and dense alignment with position map regression network":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "searching central difference convolutional networks for face anti spoofing")
  Member "learning deep models for face anti spoofing binary or auxiliary supervision":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "searching central difference convolutional networks for face anti spoofing")
  Member "racial faces in the wild reducing racial bias by information maximization adaptation network":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "learning meta face recognition in unseen domains")

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)