We are organizing a series of workshop Geometry Meets Deep Learning (GMDL). This series of workshops was initiated at ECCV 2016, followed by the second edition at ICCV 2017. The 3rd edition of the GMDL workshop will be held with ECCV 2018. The goal of this full-day workshop is to encourage the interplay between geometric vision and deep learning.
In the past few years deep learning has emerged as a common approach to learning data-driven representations. While deep learning approaches have attained remarkable performance improvements in many 2D vision tasks, such as image classification and object detection, they cannot be directly applied to geometric vision problems due to the fundamental differences between 2D and 3D vision tasks, such as the non-Euclidean nature of geometric objects, higher dimensionality, and the lack of large-scale annotated 3D datasets. Designing geometric components and constraints to improve the performance of deep neural networks is a promising direction worth further exploration. The workshop aims to bring together experts from both the geometric vision and deep learning areas to summarize recent advances, exchange ideas, and inspire new directions.
For more information please refer to the workshop website: