Handa, A., Pătrăucean, V., Stent, S. and Cipolla, R. (2016) Scenenet: An Annotated Model Generator for Indoor Scene Understanding. 2016 IEEE International Conference on Robotics and Automation, Stockholm, 16-21 May 2016, 5737-5743.
https://doi.org/10.1109/ICRA.2016.7487797

has been cited by the following article:

• 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.