All Outputs (2)

Eliminating the Blind Spot: Adapting 3D Object Detection and Monocular Depth Estimation to 360° Panoramic Imagery (2018)
Book Chapter
Payen de La Garanderie, G., Atapour Abarghouei, A., & Breckon, T. P. (2018). Eliminating the Blind Spot: Adapting 3D Object Detection and Monocular Depth Estimation to 360° Panoramic Imagery. In V. Ferrari, M. Hebert, C. Sminchisescu, & Y. Weiss (Eds.), Computer Vision – ECCV 2018 : 15th European Conference, Munich, Germany, September 8-14, 2018, Proceedings, Part XII (812-830). Springer Verlag. https://doi.org/10.1007/978-3-030-01261-8_48

Recent automotive vision work has focused almost exclusively on processing forward-facing cameras. However, future autonomous vehicles will not be viable without a more comprehensive surround sensing, akin to a human driver, as can be provided by 360... Read More about Eliminating the Blind Spot: Adapting 3D Object Detection and Monocular Depth Estimation to 360° Panoramic Imagery.

Kernelization Lower Bounds for Finding Constant-Size Subgraphs (2018)
Book Chapter
Fluschnik, T., Mertzios, G., & Nichterlein, A. (2018). Kernelization Lower Bounds for Finding Constant-Size Subgraphs. In F. Manea, R. Miller, & D. Nowotka (Eds.), Sailing routes in the world of computation : 14th Conference on Computability in Europe, CiE 2018, Kiel, Germany, July 30-August 3, 2018. Proceedings (183-193). Springer Verlag. https://doi.org/10.1007/978-3-319-94418-0_19

Kernelization is an important tool in parameterized algorithmics. Given an input instance accompanied by a parameter, the goal is to compute in polynomial time an equivalent instance of the same problem such that the size of the reduced instance only... Read More about Kernelization Lower Bounds for Finding Constant-Size Subgraphs.