OpenCodePapers

drivable-area-detection-on-bdd100k-val

Autonomous DrivingDrivable Area Detection
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PaperCodemIoUParams (M)ModelNameReleaseDate
YOLOPv2: Better, Faster, Stronger for Panoptic Driving Perception✓ Link93.238.9YOLOPv22022-08-24
TwinLiteNetPlus: A Stronger Model for Real-time Drivable Area and Lane Segmentation✓ Link92.91.94TwinLiteNetPlus-Large2024-03-25
TriLiteNet: Lightweight Model for Multi-Task Visual Perception✓ Link92.42.35TriLiteNet-base2025-03-17
TwinLiteNetPlus: A Stronger Model for Real-time Drivable Area and Lane Segmentation✓ Link92.00.48TwinLiteNetPlus-Medium2024-03-25
YOLOP: You Only Look Once for Panoptic Driving Perception✓ Link91.57.9YOLOP2021-08-25
TwinLiteNet: An Efficient and Lightweight Model for Driveable Area and Lane Segmentation in Self-Driving Cars✓ Link91.30.43TwinLiteNet2023-07-20
You Only Look at Once for Real-time and Generic Multi-Task✓ Link91A-YOLOM(s)2023-10-02
TwinLiteNetPlus: A Stronger Model for Real-time Drivable Area and Lane Segmentation✓ Link90.60.12TwinLiteNetPlus-Small2024-03-25
HybridNets: End-to-End Perception Network✓ Link90.512.8HybridNets2022-03-17
TwinLiteNetPlus: A Stronger Model for Real-time Drivable Area and Lane Segmentation✓ Link87.30.03TwinLiteNetPlus-Nano2024-03-25
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