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 "dense face alignment"):
  Abstract: Face alignment is a classic problem in the computer vision field. Previous works mostly focus on sparse alignment with a limited number of facial landmark points, i.e., facial landmark detection. In this paper, for the first time, we aim at providing a very dense 3D alignment for large-pose face images. To achieve this, we train a CNN to estimate the 3D face shape, which not only aligns limited facial landmarks but also fits face contours and SIFT feature points. Moreover, we also address the bottleneck of training CNN with multiple datasets, due to different landmark markups on different datasets, such as 5, 34, 68. Experimental results show our method not only provides high-quality, dense 3D face fitting but also outperforms the state-of-the-art facial landmark detection methods on the challenging datasets. Our model can run at real time during testing.

Includes members:
  Member "3d face morphable models in the wild":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on learning 3d face morphable model from in the wild images")
  Member "learning deep representation for face alignment with auxiliary attributes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "robust facial landmark detection via aggregation on geometrically manipulated faces")
  Member "multi directional multi level dual cross patterns for robust face recognition":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "ldop local directional order pattern for robust face retrieval")
  Member "regressing robust and discriminative 3d morphable models with a very deep neural network":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "face hallucination with finishing touches")
  Member "holistically nested edge detection":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "deep multicameral decoding for localizing unoccluded object instances from a single rgb image")
  Member "pose invariant 3d face alignment":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "hierarchical binary cnns for landmark localization with limited resources")
  Member "face alignment assisted by head pose estimation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "pfld a practical facial landmark detector")
  Member "mirror mirror on the wall tell me is the error small":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "image retargetability")

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)