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Hu, H.-N., Lin, Y.-C., Liu, M.-Y., Cheng, H.-T., Chang, Y.-J. and Sun, M. (2017) Deep 360 Pilot: Learning a Deep Agent for Piloting through 360˚ Sports Videos. In: Proceedings of 2017 IEEE Conference on Computer Vision and Pattern Recognition, ACM, New York, 1396-1405.

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• TITLE: Hyper 360—Towards a Unified Tool Set Supporting Next Generation VR Film and TV Productions

  AUTHORS: Barnabas Takacs, Zsuzsanna Vincze, Hannes Fassold, Antonis Karakottas, Nikolaos Zioulis, Dimitrios Zarpalas, Petros Daras

  KEYWORDS: Deep Learning, Tensor Flow, YoloV3, 360˚ Video, Virtual Reality, Free Viewpoint Video, Quality Control, Automatic Cinematography, Multi-Camera Systems

  JOURNAL NAME: Journal of Software Engineering and Applications, Vol.12 No.5, May 27, 2019

  ABSTRACT: We describe four fundamental challenges that complex real-life Virtual Reality (VR) productions are facing today (such as multi-camera management, quality control, automatic annotation with cinematography and 360˚depth estimation) and describe an integrated solution, called Hyper 360, to address them. We demonstrate our solution and its evaluation in the context of practical productions and present related results.