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

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Showing 41–50 of 82 papers

TitleStatusHype
An Enhanced Deep Convolutional Encoder-Decoder Network for Road Segmentation on Aerial Imagery—0
A Novel Disparity Transformation Algorithm for Road Segmentation—0
Attention-LSTM for Multivariate Traffic State Prediction on Rural Roads—0
Beyond One Glance: Gated Recurrent Architecture for Hand Segmentation—0
BiFNet: Bidirectional Fusion Network for Road Segmentation—0
Birds of A Feather Flock Together: Category-Divergence Guidance for Domain Adaptive Segmentation—0
Brightearth roads: Towards fully automatic road network extraction from satellite imagery—0
Building and Road Segmentation Using EffUNet and Transfer Learning Approach—0
Camera-Only Bird's Eye View Perception: A Neural Approach to LiDAR-Free Environmental Mapping for Autonomous Vehicles—0
Collaborative Recognition of Feasible Region with Aerial and Ground Robots through DPCN—0
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All datasetsChesapeakeRSCDeepGlobeMassachusetts Roads Dataset

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