TAG in Pattern Recognition with Applications
A workshop at the Computer Vision and Pattern Recognition (CVPR) in Vancouver, Canada on June 18th, 2023.
Call for Papers
Much of the data that is fueling the current rapid advances in mainstream data science, computer vision, and pattern recognition is high-dimensional, abundant, and relatively noise-free. However, this poses challenges in many application domains in terms of building algorithms that can capture meaningful structure from limited data and also building analytical techniques that help to understand what that structure means. Mathematicians working in topology, algebra, and geometry have more than a century’s worth of finely-developed machinery whose purpose is to give structure to, help build intuition about, and generally better understand patterns in complex data. We welcome submissions that utilize frameworks, techniques, and concepts rooted in one or more of topology, algebra, and geometry that consider a pattern recognition challenge faced in an application domain. All submitted works should include at least one real-world use-case. This session is an opportunity for researchers building robust, mathematically principled methods to present and publish work on real-world problems in pattern recognition for which standard off-the-shelf techniques do not work.
Mathematical Deep Learning, Applications
Paper Submission Deadline: February 28th, 2023 (23:59pm AOE) March 10th, 2023 (23:59pm AOE)
Author Notification: March 29th, 2023 April 1st, 2023
Camera-Ready Paper Deadline: April 8th, 2023 (18:00 PST)
Workshop Date: Sunday June 18th, 2023
Papers: The page limit for papers is 8 pages (not including references) using the CVPR proceedings style file which can be downloaded here. Please also note that paper submissions are double-blind in accordance with the main conference requirements.
Conference: The 2023 International Conference on Computer Vision and Pattern Recognition will be held in Vancouver, British Columbia, Canada June 18-22, 2023 and will be held in a hybrid format with all presentations given live (not pre-recorded) and an in-person only poster session.
Submission site: https://cmt3.research.microsoft.com/TAGPRA2023