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pro vyhledávání: '"Hemachandra, Sahan"'
Autor:
Jayasinghe, Oshada, Hemachandra, Sahan, Anhettigama, Damith, Kariyawasam, Shenali, Wickremasinghe, Tharindu, Ekanayake, Chalani, Rodrigo, Ranga, Jayasekara, Peshala
Recent work done on traffic sign and traffic light detection focus on improving detection accuracy in complex scenarios, yet many fail to deliver real-time performance, specifically with limited computational resources. In this work, we propose a sim
Externí odkaz:
http://arxiv.org/abs/2205.02421
Autor:
Jayasinghe, Oshada, Hemachandra, Sahan, Anhettigama, Damith, Kariyawasam, Shenali, Rodrigo, Ranga, Jayasekara, Peshala
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, unavailabi
Externí odkaz:
http://arxiv.org/abs/2110.11867
Autor:
Jayasinghe, Oshada, Anhettigama, Damith, Hemachandra, Sahan, Kariyawasam, Shenali, Rodrigo, Ranga, Jayasekara, Peshala
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. In this work, we propose SwiftLane: a simple and light
Externí odkaz:
http://arxiv.org/abs/2110.11779
Light field saliency detection -- important due to utility in many vision tasks -- still lacks speed and can improve in accuracy. Due to the formulation of the saliency detection problem in light fields as a segmentation task or a memorizing task, ex
Externí odkaz:
http://arxiv.org/abs/2010.13073
Publikováno v:
In Signal Processing: Image Communication January 2023 110
Autor:
Jayasinghe, Oshada, Hemachandra, Sahan, Anhettigama, Damith, Kariyawasam, Shenali, Rodrigo, Ranga, Jayasekara, Peshala
Publikováno v:
2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).
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, unavailabi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::70fa6cb411744652efb07f649433082c
https://doi.org/10.1109/wacv51458.2022.00344
https://doi.org/10.1109/wacv51458.2022.00344