mlsanityData to 14 Oct 2026

BED-SAM2: Boundary-Enhanced-Depth SAM2 via Monocular Geometric Priors

arXiv 2605.24893 ↗First posted 24 May 2026cs.CVcited by 0

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Abstract (arXiv)

Building upon the SAM2 vision foundation model for downstream segmentation, this study introduces Boundary Enhanced Depth (BED)-SAM2. The SAM2 Hiera encoder architecture is modified to directly encode monocular depth information from RGB images, thereby providing geometric cues that enhance object boundary delineation and facilitate the extraction of camouflaged object shapes. BED-SAM2 demonstrates competitive state-of-the-art performance across multiple salient and camouflaged object detection tasks with as few as five training epochs.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 35 of its 54 references that are in the map. First posted on arXiv 24 May 2026.

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35 of 54 references.

References · 35

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23 more
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