1 code implementation • 5 May 2022 • Oshada Jayasinghe, Sahan Hemachandra, Damith Anhettigama, Shenali Kariyawasam, Tharindu Wickremasinghe, Chalani Ekanayake, Ranga Rodrigo, Peshala Jayasekara
In this work, we propose a simple deep learning based end-to-end detection framework, which effectively tackles challenges inherent to traffic sign and traffic light detection such as small size, large number of classes and complex road scenarios.
no code implementations • 22 Oct 2021 • Oshada Jayasinghe, Damith Anhettigama, Sahan Hemachandra, Shenali Kariyawasam, Ranga Rodrigo, Peshala Jayasekara
Recent work done on lane detection has been able to detect lanes accurately in complex scenarios, yet many fail to deliver real-time performance specifically with limited computational resources.
Ranked #43 on Lane Detection on CULane
1 code implementation • 22 Oct 2021 • Oshada Jayasinghe, Sahan Hemachandra, Damith Anhettigama, Shenali Kariyawasam, Ranga Rodrigo, Peshala Jayasekara
In this paper, we introduce a novel road marking benchmark dataset for road marking detection, addressing the limitations in the existing publicly available datasets such as lack of challenging scenarios, prominence given to lane markings, unavailability of an evaluation script, lack of annotation formats and lower resolutions.
no code implementations • 25 Oct 2020 • Sahan Hemachandra, Ranga Rodrigo, Chamira Edussooriya
Light field saliency detection -- important due to utility in many vision tasks -- still lacks speed and can improve in accuracy.