Mr Grégoire Payen de La Garanderie
(email at firstname.lastname@example.org)
I am a Computer Science PhD student in my final year of study at Durham University. Prior, I worked as a Graduate Research Engineer at Imagination Technologies. I received a MSc from Cranfield University in 2013. I work on situational awareness for autonomous driving. My primary research interests are centered around perception for self-driving vehicles, computer vision, machine learning and more specifically deep learning, object detection and tracking, visual question answering and related challenges. This project is sponsored by Jaguar Land Rover and EPSRC.
- Computer Vision
- Deep Learning
- Image Processing
- Machine Learning
Chapter in book
- Payen de La Garanderie, Grégoire, Atapour Abarghouei, Amir & Breckon, Toby P. (2018). Eliminating the Blind Spot: Adapting 3D Object Detection and Monocular Depth Estimation to 360° Panoramic Imagery. In Computer Vision – ECCV 2018: 15th European Conference, Munich, Germany, September 8-14, 2018, Proceedings, Part XII. Ferrari, Vittorio, Hebert, Martial, Sminchisescu, Cristian & Weiss, Yair Cham: Springer. 11217: 812-830.
- Atapour-Abarghouei, Amir, de La Garanderie, Gregoire Payen & Breckon, Toby P. (2016), Back to Butterworth - a Fourier basis for 3D surface relief hole filling within RGB-D imagery, 2016 23rd International Conference on Pattern Recognition (ICPR). 2813.
- Payen de La Garanderie, G. & Breckon, T.P. (2014), Improved Depth Recovery In Consumer Depth Cameras via Disparity Space Fusion within Cross-spectral Stereo, in Valstar, Michel, French, Andrew & Pridmore, Tony eds, Proceedings of the British Machine Vision Conference. BMVA Press, 417.1-417.12.