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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–10 of 82 papers

TitleStatusHype
Road Segmentation for ADAS/AD Applications—0
Technical Report for ICRA 2025 GOOSE 2D Semantic Segmentation Challenge: Boosting Off-Road Segmentation via Photometric Distortion and Exponential Moving Average—0
Camera-Only Bird's Eye View Perception: A Neural Approach to LiDAR-Free Environmental Mapping for Autonomous Vehicles—0
InterLoc: LiDAR-based Intersection Localization using Road Segmentation with Automated Evaluation Method—0
Long-Range LiDAR Vehicle Detection Through Clustering and Classification for Autonomous Racing—0
Pix2Poly: A Sequence Prediction Method for End-to-end Polygonal Building Footprint Extraction from Remote Sensing ImageryCode2
Trajectory-based Road Autolabeling with Lidar-Camera Fusion in Winter ConditionsCode1
Pathfinder for Low-altitude Aircraft with Binary Neural NetworkCode0
UdeerLID+: Integrating LiDAR, Image, and Relative Depth with Semi-Supervised—0
Brightearth roads: Towards fully automatic road network extraction from satellite imagery—0
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All datasetsChesapeakeRSCDeepGlobeMassachusetts Roads Dataset

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1RSM-SSIoU67.35—Unverified
2SPIN Road Mapper (ours)IoU65.24—Unverified