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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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 26–50 of 82 papers

TitleStatusHype
R2S100K: Road-Region Segmentation Dataset For Semi-Supervised Autonomous Driving in the Wild—0
Building and Road Segmentation Using EffUNet and Transfer Learning Approach—0
Polarimetric Imaging for Perception—0
PaRK-Detect: Towards Efficient Multi-Task Satellite Imagery Road Extraction via Patch-Wise Keypoints Detection—0
Attention-LSTM for Multivariate Traffic State Prediction on Rural Roads—0
Atmospheric Transmission and Thermal Inertia Induced Blind Road Segmentation with a Large-Scale Dataset TBRSDCode0
Visual Traffic Knowledge Graph Generation from Scene Images—0
Semi-Supervised Confidence-Level-based Contrastive Discrimination for Class-Imbalanced Semantic SegmentationCode2
Monocular BEV Perception of Road Scenes via Front-to-Top View Projection—0
PatchRefineNet: Improving Binary Segmentation by Incorporating Signals from Optimal Patch-wise BinarizationCode0
Deep Learning Computer Vision Algorithms for Real-time UAVs On-board Camera Image Processing—0
Unstructured Road Segmentation using Hypercolumn based Random Forests of Local expertsCode0
Solving Learn-to-Race Autonomous Racing Challenge by Planning in Latent Space—0
Efficient fine-grained road segmentation using superpixel-based CNN and CRF models—0
Improving Road Segmentation in Challenging Domains Using Similar Place Priors—0
Birds of A Feather Flock Together: Category-Divergence Guidance for Domain Adaptive Segmentation—0
Fast Road Segmentation via Uncertainty-aware Symmetric NetworkCode1
Road-aware Monocular Structure from Motion and Homography Estimation—0
SPIN Road Mapper: Extracting Roads from Aerial Images via Spatial and Interaction Space Graph Reasoning for Autonomous DrivingCode1
Stagewise Unsupervised Domain Adaptation with Adversarial Self-Training for Road Segmentation of Remote Sensing ImagesCode1
Projecting Your View Attentively: Monocular Road Scene Layout Estimation via Cross-View TransformationCode1
Collaborative Recognition of Feasible Region with Aerial and Ground Robots through DPCN—0
SS-SFDA : Self-Supervised Source-Free Domain Adaptation for Road Segmentation in Hazardous EnvironmentsCode1
PREGAN: Pose Randomization and Estimation for Weakly Paired Image Style TranslationCode1
Road Segmentation for Remote Sensing Images using Adversarial Spatial Pyramid NetworksCode1
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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