One Day Meeting: Deep Learning in 3-Dimensions
Wednesday 20 February 2019
Chairs: Chris Holder, Chris Willcocks and Gregoire Payen de La Garanderie
- Adrian Hilton, University of Surrey
- Alex Kendall, University of Cambridge, Wayve
After the meeting the organisers prepare a short summary of the meeting. The report is available here.
Videos of Talks
On our BMVA youtube channel there are recorded talks of the slides and speaker from the day here.
Deep learning has revolutionised the world of artificial intelligence in recent years, providing a huge boost to machine learning research as well as to real-world applications of such technology. In this meeting we aim to explore the key challenges of combining deep learning with 3D vision.
|Keynote: Adrian Hilton: Deep Learning in 4D
|Adrian Penate Sanchez University of Oxfords: 3D Pick & Mix: Object Part Blending in Joint Shape and Image Manifolds
|Olivia Wiles, University of Oxford: Learning to infer the 3D shape of sculptures
|Andrew Gilbert, University of Surrey: Volumetric performance capture from minimal camera viewpoints
|Viswadeep Sarangi, University of York: Clinical evaluation of machine learning approaches for the classification of 3D gait using static & dynamic models in comparison to human perception
|Keynote: Alex Kendall
|Posters and Coffee
|Plug-and-Train Loss for Single View 3D Reconstruction, Eduard Ramon Maldonado, Universitat Politècnica de Catalunya; Deep learning for ground classification in 3D point clouds of large-scale heritage sites, Dimitrios Makris, University of the Aegean; Improved Object Detection with 3D Deep Neural Networks, Justin Le Louëdec, University of Lincoln; Recovery of superquadric parameters from range images using deep learning, Franc Solina, University of Ljubljana
|Michael Edward, Swansea University: Graph Convolutional Neural Networks for 3D Medical Images
|Georgi Tinchev, University of Oxford: Learning to See the Wood for the Trees: Deep Laser
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