human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "3d gmnet learning to estimate 3d shape from a single image as a gaussian mixture"
  Abstract: In this paper, we introduce 3D-GMNet, a deep neural network for single-image 3D shape recovery. As the name suggests, 3D-GMNet recovers 3D shape as a Gaussian mixture model. In contrast to voxels, point clouds, or meshes, a Gaussian mixture representation requires a much smaller footprint for representing 3D shapes and, at the same time, offers a number of additional advantages including instant pose estimation, automatic level-of-detail computation, and a distance measure. The proposed 3D-GMNet is trained end-to-end with single input images and corresponding 3D models by using two novel loss functions: a 3D Gaussian mixture loss and a multi-view 2D loss. The first maximizes the likelihood of the Gaussian mixture shape representation by considering the target point cloud as samples from the true distribution, and the latter improves the consistency between the input silhouette and the projection of the Gaussian mixture shape model. Extensive quantitative evaluations with synthesized and real images demonstrate the effectiveness of the proposed method.

Question: Please tell me which class the center node 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)