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: "optimizing for aesthetically pleasing quadrotor camera motion"
  Abstract: We propose an algorithm that optimizes positional and temporal reference fit jointly to generate globally smooth quadrotor camera trajectories. Videos are perceived as better looking than results of the state-of-the-art.

Connected through hyperedge HE-1 (induced by source paper "autonomous aerial cinematography in unstructured environments with learned artistic decision making"):
  with members:
    - "improved generalization of heading direction estimation for aerial filming using semi supervised regression"
    - "can a robot become a movie director learning artistic principles for aerial cinematography"
    - "towards a robust aerial cinematography platform localizing and tracking moving targets in unstructured environments"
    - "autonomous drone cinematographer using artistic principles to create smooth safe occlusion free trajectories for aerial filming"
    - "integrating kinematics and environment context into deep inverse reinforcement learning for predicting off road vehicle trajectories"
    - "good semi supervised learning that requires a bad gan"
    - "mobilenets efficient convolutional neural networks for mobile vision applications"
    - "airsim high fidelity visual and physical simulation for autonomous vehicles"

Connected through hyperedge HE-2 (induced by source paper "activemocap optimized drone flight for active human motion capture"):
  with members:
    - "3d human pose estimation in video with temporal convolutions and semi supervised training"
    - "yolov3 an incremental improvement"
    - "learn to score efficient 3d scene exploration by predicting view utility"
    - "human motion capture using a drone"
    - "deep directional statistics pose estimation with uncertainty quantification"
    - "plan3d viewpoint and trajectory optimization for aerial multi view stereo reconstruction"
    - "lifting from the deep convolutional 3d pose estimation from a single image"
    - "harvesting multiple views for marker less 3d human pose annotations"

Connected through hyperedge HE-3 (induced by source paper "towards a robust aerial cinematography platform localizing and tracking moving targets in unstructured environments"):
  with members:
    - "improved generalization of heading direction estimation for aerial filming using semi supervised regression"
    - "autonomous drone cinematographer using artistic principles to create smooth safe occlusion free trajectories for aerial filming"
    - "yolov3 an incremental improvement"
    - "shufflenet an extremely efficient convolutional neural network for mobile devices"
    - "mobilenets efficient convolutional neural networks for mobile vision applications"
    - "directing cinematographic drones"
    - "voxblox incremental 3d euclidean signed distance fields for on board mav planning"
    - "automated cinematography with unmanned aerial vehicles"

Connected through hyperedge HE-4 (induced by source paper "can a robot become a movie director learning artistic principles for aerial cinematography"):
  with members:
    - "towards a robust aerial cinematography platform localizing and tracking moving targets in unstructured environments"
    - "learning agile and dynamic motor skills for legged robots"
    - "autonomous drone cinematographer using artistic principles to create smooth safe occlusion free trajectories for aerial filming"
    - "learning robust rewards with adversarial inverse reinforcement learning"
    - "airsim high fidelity visual and physical simulation for autonomous vehicles"
    - "control of a quadrotor with reinforcement learning"
    - "directing cinematographic drones"
    - "creatism a deep learning photographer capable of creating professional work"

Connected through hyperedge HE-5 (induced by source paper "dynamic drawing guidance via electromagnetic haptic feedback"):
  with members:
    - "deepwriting making digital ink editable via deep generative modeling"

Connected through hyperedge HE-6 (induced by source paper "autonomous drone cinematographer using artistic principles to create smooth safe occlusion free trajectories for aerial filming"):
  with members:
    - "fast autonomous flight in gps denied and cluttered environments"
    - "mobilenets efficient convolutional neural networks for mobile vision applications"
    - "airsim high fidelity visual and physical simulation for autonomous vehicles"
    - "directing cinematographic drones"
    - "automated cinematography with unmanned aerial vehicles"
    - "ssd single shot multibox detector"
    - "yolo9000 better faster stronger"
    - "airways optimization based planning of quadrotor trajectories according to high level user goals"

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.GR(Graphics)