no code implementations • 24 Feb 2023 • Arindam Das, Sudip Das, Ganesh Sistu, Jonathan Horgan, Ujjwal Bhattacharya, Edward Jones, Martin Glavin, Ciarán Eising
Multimodal learning, particularly for pedestrian detection, has recently received emphasis due to its capability to function equally well in several critical autonomous driving scenarios such as low-light, night-time, and adverse weather conditions.
no code implementations • 15 Jun 2022 • Arindam Das, Sudip Das, Ganesh Sistu, Jonathan Horgan, Ujjwal Bhattacharya, Edward Jones, Martin Glavin, Ciarán Eising
The proposed framework has improved state-of-the-art performances of pose estimation, pedestrian detection, and instance segmentation.
Ranked #18 on Pose Estimation on COCO test-dev
2 code implementations • 20 May 2022 • Shane Gilroy, Darragh Mullins, Edward Jones, Ashkan Parsi, Martin Glavin
Accurate detection and classification of vulnerable road users is a safety critical requirement for the deployment of autonomous vehicles in heterogeneous traffic.
no code implementations • 11 May 2022 • Shane Gilroy, Martin Glavin, Edward Jones, Darragh Mullins
Pedestrian detection is among the most safety-critical features of driver assistance systems for autonomous vehicles.
2 code implementations • 10 May 2022 • Shane Gilroy, Darragh Mullins, Edward Jones, Ashkan Parsi, Martin Glavin
RetinaNet has the lowest overall detection performance across the range of occlusion levels.