SOTAVerified

Road Segmentation

Road Segmentation is a pixel wise binary classification in order to extract underlying road network. Various Heuristic and data driven models are proposed. Continuity and robustness still remains one of the major challenges in the area.

Papers

Showing 51–60 of 82 papers

TitleStatusHype
DeepCompass: AI-driven Location-Orientation Synchronization for Navigating Platforms—0
Deep Learning Computer Vision Algorithms for Real-time UAVs On-board Camera Image Processing—0
Distantly Supervised Road Segmentation—0
Dual Local-Global Contextual Pathways for Recognition in Aerial Imagery—0
Efficient fine-grained road segmentation using superpixel-based CNN and CRF models—0
Road Segmentation for ADAS/AD Applications—0
Road Segmentation in SAR Satellite Images with Deep Fully-Convolutional Neural Networks—0
Road Segmentation of Remotely-Sensed Images Using Deep Convolutional Neural Networks with Landscape Metrics and Conditional Random Fields—0
Road Segmentation on low resolution Lidar point clouds for autonomous vehicles—0
Road Segmentation Using CNN with GRU—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1U-Net (ResNet-18)DWR46.5—Unverified
2DeepLabV3+ (ResNet-18)DWR46.1—Unverified
3U-Net (ResNet-50)DWR45.7—Unverified
4FCNDWR10.7—Unverified
#ModelMetricClaimedVerifiedStatus
1CoANet + PRNmIoU70.6—Unverified
2SPIN Road Mapper (ours)APLS0.74—Unverified
3D-LinkNetIoU0.64—Unverified
#ModelMetricClaimedVerifiedStatus
1RSM-SSIoU67.35—Unverified
2SPIN Road Mapper (ours)IoU65.24—Unverified