Feb 14, 2022 · We propose a multi-task learning method of road segmentation, direction estimation and road edge learning to make our model connect roads ...
Dec 9, 2024 · We propose a multi-task learning method of road segmentation, direction estimation and road edge learning to make our model connect roads ...
(1)We propose a multi-task learning method that con- tains three related tasks road segmentation, road direction es- timation, and road edge detection to make ...
This study presents a cost-effective and highly accurate solution for road segmentation by integrating data from multiple sensors within a multi-task learning ...
Missing: Multimodal | Show results with:Multimodal
These models possess multi-task learning capabilities, allowing them to concurrently perform multiple tasks. Moreover, with the integration of multi-modal ...
This repository contains the implementation of the 3MT-RoadSeg method in Pytorch. 3MT-RoadSeg is a fast and accurate method that does not need any ...
Missing: Multimodal | Show results with:Multimodal
To address this, we propose a novel multi-task learning framework for road scenarios, named CFFM, which simultaneously trains detection and segmentation tasks.
The road segmentation task is to extract the road surface from the image at pixel level. In road segmentation for remote sensing images, deep learning-based ...
This study presents a cost-effective and highly accurate solution for road segmentation by integrating data from multiple sensors within a multi-task learning ...
Missing: Multimodal | Show results with:Multimodal
The intention behind the fusion is to allow the flow of information between both tasks to improve the performance of an individual task in a multi-task learning ...
Missing: Multimodal | Show results with:Multimodal