Browse State-of-the-Art › Road Segmentation
Road Segmentation
34 papers with code · 3 benchmarks · 5 datasets archive 2025-07-28
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.
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
3 leaderboard tables shown for this task, 3 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.
| Dataset | Best model (first row in archive order) | Paper | Code | Syntology | Compare |
|---|---|---|---|---|---|
| ChesapeakeRSC (4 rows) | U-Net (ResNet-18) | Seeing the roads through the trees: A benchmark for modeling... | code | — | Compare |
| DeepGlobe (3 rows) | SPIN Road Mapper (ours) | SPIN Road Mapper: Extracting Roads from Aerial Images via Spatial... | code | — | Compare |
| Massachusetts Roads Dataset (2 rows) | RSM-SS | RS-Mamba for Large Remote Sensing Image Dense Prediction | code | Syntology ran 2 of 6 samples · 4 unverified | Compare |
Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
5 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
1 subtask in the archive's task tree.
Parent tasks archive 2025-07-28
Most implemented papers archive 2025-07-28
30 shown of 34 papers with code (82 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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22 Dec 2016 15 repositories listed Syntology ran 6 of 42 samples · 36 unverifiedWhile most approaches to semantic reasoning have focused on improving performance, in this paper we argue that computational times are very important in order to enable real time applications such as autonomous driving.
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8 Dec 2018 5 repositories listedRoad extraction is a fundamental task in the field of remote sensing which has been a hot research topic in the past decade.
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29 Apr 2024 2 repositories listed Syntology ran 5 of 10 samples · 5 unverified · 10 pointer-only (licence)Topological consistency plays a crucial role in the task of boundary segmentation for reticular images, such as cell membrane segmentation in neuron electron microscopic images, grain boundary segmentation in material…
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12 Jan 2024 2 repositories listedIn this work we propose a road segmentation benchmark dataset, Chesapeake Roads Spatial Context (RSC), for evaluating the spatial long-range context understanding of geospatial machine learning models and show how…
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9 Jan 2024 2 repositories listedMassive amounts of unlabelled data are captured by Earth Observation (EO) satellites, with the Sentinel-2 constellation generating 1.
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27 Nov 2020 2 repositories listedWe present a novel approach for unsupervised road segmentation in adverse weather conditions such as rain or fog.
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10 Aug 2018 2 repositories listedIn automated driving systems (ADS) and advanced driver-assistance systems (ADAS), an efficient road segmentation is necessary to perceive the drivable region and build an occupancy map for path planning.
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13 Dec 2017 2 repositories listed Syntology ran 2 of 2 samples · 0 unverifiedThe field of deep learning has seen significant advancement in recent years.
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10 Dec 2024 1 repository listedExtraction of building footprint polygons from remotely sensed data is essential for several urban understanding tasks such as reconstruction, navigation, and mapping.
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3 Dec 2024 1 repository listedRobust road segmentation in all road conditions is required for safe autonomous driving and advanced driver assistance systems.
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13 Sep 2024 1 repository listedA prior global topological map (e.
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3 Apr 2024 1 repository listed Syntology ran 2 of 6 samples · 4 unverified · 6 pointer-only (licence)RSM is specifically designed to capture the global context of remote sensing images with linear complexity, facilitating the effective processing of large VHR images.
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28 Mar 2024 1 repository listedMoreover, we compare our MMCert with a state-of-the-art certified defense extended from unimodal models.
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4 Feb 2024 1 repository listedThe spatial detail branch is firstly designed to extract low-level feature representation for the road by the first stage of ResNet-18.
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28 Dec 2023 1 repository listedThis study presents an innovative approach for automatic road detection with deep learning, by employing fusion strategies for utilizing both lower-resolution satellite imagery and GPS trajectory data, a concept never…
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7 Dec 2023 1 repository listedRoad network extraction from satellite images is widely applicated in intelligent traffic management and autonomous driving fields.
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8 Nov 2023 1 repository listedOne of the fundamental tasks in computer vision is semantic image segmentation, which is vital for precise object delineation.
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23 Aug 2023 1 repository listedThe inference times obtained in all experiments are very promising for real-time experiments.
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1 Jan 2023 1 repository listedThe experimental results demonstrate that our method outperforms existing techniques and achieves state-of-the-art performance in thermal blind road segmentation, as validated on benchmark thermal infrared semantic…
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28 Nov 2022 1 repository listedFirst and foremost, to make the model operate in a semi-supervised manner, we proposed the confidence-level-based contrastive learning to achieve instance discrimination in an explicit manner, and make the…
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12 Nov 2022 1 repository listedGiven the logit scores produced by the base segmentation model, each pixel is given a pseudo-label that is obtained by optimally thresholding the logit scores in each image patch.
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23 Jul 2022 1 repository listedWe propose a method to detect and segment roads with a random forest classifier of local experts with superpixel based machine-learned features.
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9 Mar 2022 1 repository listedThe high performance of RGB-D based road segmentation methods contrasts with their rare application in commercial autonomous driving, which is owing to two reasons: 1) the prior methods cannot achieve high inference…
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16 Sep 2021 1 repository listedUsing just convolution neural networks (ConvNets) for this problem is not effective as it is inefficient at capturing distant dependencies between road segments in the image which is essential to extract road…
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28 Aug 2021 1 repository listedIn this paper, we propose a novel stagewise domain adaptation model called RoadDA to address the DS issue in this field.
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19 Jun 2021 1 repository listedFurthermore, our model runs at 35 FPS on a single GPU, which is efficient and applicable for real-time panorama HD map reconstruction.
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31 Oct 2020 1 repository listedUtilizing the trained model under different conditions without data annotation is attractive for robot applications.
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10 Aug 2020 1 repository listedWe also propose a feature pyramid network that improves the performance of the proposed model by extracting effective features from all the layers of the network for describing different scales objects.
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13 Jun 2020 1 repository listedIn order to reach real-time process speed, a light-weight, high-throughput CNN architecture namely RoadNet-RT is proposed for road segmentation in this paper.
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30 Mar 2020 1 repository listedAutonomous vehicles commonly rely on highly detailed birds-eye-view maps of their environment, which capture both static elements of the scene such as road layout as well as dynamic elements such as other cars and…
Syntology lines on 4 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections