Drivable Area Detection

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

1 leaderboard table shown for this task, 1 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.

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 2026-09-25.

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

1 dataset whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

8 shown of 8 papers with code (12 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.

• YOLOP: You Only Look Once for Panoptic Driving Perception
  25 Aug 2021 5 repositories listed Syntology ran 8 of 18 samples · 10 unverified
  A panoptic driving perception system is an essential part of autonomous driving.
• BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning
  12 May 2018 4 repositories listed Syntology ran 0 of 2 samples · 2 unverified
  Datasets drive vision progress, yet existing driving datasets are impoverished in terms of visual content and supported tasks to study multitask learning for autonomous driving.
• HybridNets: End-to-End Perception Network
  17 Mar 2022 3 repositories listed
  Based on these optimizations, we have developed an end-to-end perception network to perform multi-tasking, including traffic object detection, drivable area segmentation and lane detection simultaneously, called…
• TwinLiteNetPlus: A Stronger Model for Real-time Drivable Area and Lane Segmentation
  25 Mar 2024 2 repositories listed
  Semantic segmentation is crucial for autonomous driving, particularly for Drivable Area and Lane Segmentation, ensuring safety and navigation.
• YOLOPv2: Better, Faster, Stronger for Panoptic Driving Perception
  24 Aug 2022 2 repositories listed
  Over the last decade, multi-tasking learning approaches have achieved promising results in solving panoptic driving perception problems, providing both high-precision and high-efficiency performance.
• TriLiteNet: Lightweight Model for Multi-Task Visual Perception
  17 Mar 2025 1 repository listed
  Specifically, the TriLiteNetbase demonstrated a recall of 85.
• You Only Look at Once for Real-time and Generic Multi-Task
  2 Oct 2023 1 repository listed
  In this study, we incorporate A-YOLOM, an adaptive, real-time, and lightweight multi-task model designed to concurrently address object detection, drivable area segmentation, and lane line segmentation tasks.
• TwinLiteNet: An Efficient and Lightweight Model for Driveable Area and Lane Segmentation in Self-Driving Cars
  20 Jul 2023 1 repository listed
  Driveable Area Segmentation and Lane Detection are particularly important for safe and efficient navigation on the road.

Syntology lines on 2 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 2026-09-25.