Call For Paper

In recent years, deep learning has made unprecedented progress in artificial intelligence tasks from speech recognition to image retrieval. However, existing methods poorly serve the three-dimensional data that drives a broad range of critical applications including 3D object recognition, autonomous driving, graphics, robotics, medical imaging, neuroscience, and scientific simulations. These problems have drawn attention of researchers in different fields such as neuroscience, computer vision and graphics. Through those studies, new ideas and discoveries have kept emerging, which can inspire advances in the other fields. We aim to build a venue for publishing original research results in 3D deep learning, as well as exhibiting the latest trends and ideas. To be specific, we are interested in the following topics using 3D deep learning methods:

The workshop will include invited talks, oral presentations, and posters. We accept two tracks of submissions to the workshop on those topics: paper (6 - 9 pages) and extended abstract (4 pages). The submitted papers should present original research that has not been published before. The paper submission can be based around existing works, but it should present some novel ideas. High-quality papers will be selected for oral presentation. The extended abstracts can describe some new ideas or the latest published paper. We encourage submissions of works that has been previously published or is to be presented in the main conference. All the submission should follow NIPS 2016 style template. The accepted papers and abstracts will be available publicly on the workshop website. Please make submissions through CMT system for 3DDL2016.


Submission Deadline (Both Tracks)10/01/2016
Final Decisions Announced10/21/2016
Workshop Date12/09/2016