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 5160 of 82 papers

TitleStatusHype
TopoAL: An Adversarial Learning Approach for Topology-Aware Road Segmentation0
RoadNet-RT: High Throughput CNN Architecture and SoC Design for Real-Time Road SegmentationCode0
VecRoad: Point-Based Iterative Graph Exploration for Road Graphs Extraction0
Road Segmentation on low resolution Lidar point clouds for autonomous vehicles0
BiFNet: Bidirectional Fusion Network for Road Segmentation0
Predicting Semantic Map Representations from Images using Pyramid Occupancy NetworksCode1
Multi-Feature View-Based Shallow Convolutional Neural Network for Road Segmentation0
Introducing Fuzzy Layers for Deep Learning0
PT-ResNet: Perspective Transformation-Based Residual Network for Semantic Road Image Segmentation0
Spatial Information Inference Net: Road Extraction Using Road-Specific Contextual InformationCode0
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Benchmark Results

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