DAS-SAM: fine-tuning SAM towards drivable area segmentation via efficient multi-scale traffic scene-aware adaptation

Abstract Drivable area segmentation (DAS) plays an important role in autonomous driving. Segment anything model (SAM) has recently emerged as a powerful foundation model, demonstrating remarkable potential across diverse downstream segmentation tasks through domain-specific parameter-efficient fine-...

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Principais autores:	Zhenghao Chen, Nan Zhou, Yi Fan, Lina Zhou, Yubao Xie, Jiaxin Chen, Di Huang
格式:	Artigo
語言:	Inglês
出版:	Springer 2026-02-01
叢編:	Visual Intelligence
主題:	Drivable area segmentation (DAS) Parameter-efficient fine-tuning (PEFT) Segment anything model (SAM) Multi-scale feature extraction Traffic scene context
在線閱讀:	https://doi.org/10.1007/s44267-026-00109-1
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