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 51–82 of 82 papers

TitleStatusHype
Road-aware Monocular Structure from Motion and Homography Estimation—0
Collaborative Recognition of Feasible Region with Aerial and Ground Robots through DPCN—0
TopoAL: An Adversarial Learning Approach for Topology-Aware Road Segmentation—0
RoadNet-RT: High Throughput CNN Architecture and SoC Design for Real-Time Road SegmentationCode0
VecRoad: Point-Based Iterative Graph Exploration for Road Graphs Extraction—0
Road Segmentation on low resolution Lidar point clouds for autonomous vehicles—0
BiFNet: Bidirectional Fusion Network for Road Segmentation—0
Multi-Feature View-Based Shallow Convolutional Neural Network for Road Segmentation—0
Introducing Fuzzy Layers for Deep Learning—0
PT-ResNet: Perspective Transformation-Based Residual Network for Semantic Road Image Segmentation—0
Spatial Information Inference Net: Road Extraction Using Road-Specific Contextual InformationCode0
NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local OperationsCode0
Recurrent U-Net for Resource-Constrained Segmentation—0
Road Segmentation with Image-LiDAR Data Fusion—0
D-LinkNet: LinkNet with Pretrained Encoder and Dilated Convolution for High Resolution Satellite Imagery Road ExtractionCode0
Beyond One Glance: Gated Recurrent Architecture for Hand Segmentation—0
Road Segmentation Using CNN and Distributed LSTMCode0
A Novel Disparity Transformation Algorithm for Road Segmentation—0
Semantic Binary Segmentation using Convolutional Networks without DecodersCode0
Road Segmentation Using CNN with GRU—0
RoadTracer: Automatic Extraction of Road Networks from Aerial ImagesCode0
Road Segmentation in SAR Satellite Images with Deep Fully-Convolutional Neural Networks—0
Self-Supervised Relative Depth Learning for Urban Scene Understanding—0
Deep Quaternion NetworksCode0
A Joint 3D-2D based Method for Free Space Detection on Roads—0
Distantly Supervised Road Segmentation—0
Road Segmentation of Remotely-Sensed Images Using Deep Convolutional Neural Networks with Landscape Metrics and Conditional Random Fields—0
An Enhanced Deep Convolutional Encoder-Decoder Network for Road Segmentation on Aerial Imagery—0
HD Maps: Fine-Grained Road Segmentation by Parsing Ground and Aerial Images—0
Dual Local-Global Contextual Pathways for Recognition in Aerial Imagery—0
On the Diagnostic of Road Pathway Visibility—0
Accurate Urban Road Centerline Extraction from VHR Imagery via Multiscale Segmentation and Tensor Voting—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