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: "visual distortions in 360 degree videos"
  Abstract: Omnidirectional (or 360-degree) images and videos are emergent signals in many areas such as robotics and virtual/augmented reality. In particular, for virtual reality, they allow an immersive experience in which the user is provided with a 360-degree field of view and can navigate throughout a scene, e.g., through the use of Head Mounted Displays. Since it represents the full 360-degree field of view from one point of the scene, omnidirectional content is naturally represented as spherical visual signals. Current approaches for capturing, processing, delivering, and displaying 360-degree content, however, present many open technical challenges and introduce several types of distortions in these visual signals. Some of the distortions are specific to the nature of 360-degree images, and often different from those encountered in the classical image communication framework. This paper provides a first comprehensive review of the most common visual distortions that alter 360-degree signals undergoing state of the art processing in common applications. While their impact on viewers' visual perception and on the immersive experience at large is still unknown ---thus, it stays an open research topic--- this review serves the purpose of identifying the main causes of visual distortions in the end-to-end 360-degree content distribution pipeline. It is essential as a basis for benchmarking different processing techniques, allowing the effective design of new algorithms and applications. It is also necessary to the deployment of proper psychovisual studies to characterise the human perception of these new images in interactive and immersive applications.

Connected through hyperedge HE-1 (induced by source paper "methodology for accurately assessing the quality perceived by users on 360vr contents"):
  with members:
    - "streaming virtual reality content"

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.MM(Multimedia)