1 code implementation • 7 Apr 2024 • Saravanabalagi Ramachandran, Jonathan Horgan, Ganesh Sistu, John McDonald
Based on our empirical analysis of multiple runs, we identify that continuity and distinctiveness are crucial characteristics for an optimal global descriptor that enable efficient and scalable hierarchical mapping, and present a methodology for quantifying and contrasting these characteristics across different global descriptors.
no code implementations • 31 Dec 2023 • Saravanabalagi Ramachandran, Nathaniel Cibik, Ganesh Sistu, John McDonald
Motion segmentation is a complex yet indispensable task in autonomous driving.
no code implementations • 26 Oct 2022 • Saravanabalagi Ramachandran, Jonathan Horgan, Ganesh Sistu, John McDonald
We train a Variational Autoencoder in an unsupervised manner and map images to a constrained multi-dimensional latent space and use the latent vectors as compact embeddings that serve as global descriptors for images.
no code implementations • 26 Jun 2022 • Saravanabalagi Ramachandran, Ganesh Sistu, Varun Ravi Kumar, John McDonald, Senthil Yogamani
Object detection is a comprehensively studied problem in autonomous driving.
no code implementations • 17 Jul 2021 • Saravanabalagi Ramachandran, Ganesh Sistu, John McDonald, Senthil Yogamani
This challenge served as a medium to investigate the challenges and new methodologies to handle the complexities with perception on fisheye images.
1 code implementation • 15 Jul 2021 • Saravanabalagi Ramachandran, John McDonald
OdoViz is a reactive web-based tool for 3D visualization and processing of autonomous vehicle datasets designed to support common tasks in visual place recognition research.