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SPLG-Mamba: Structure-Preserving Local-Global Mamba Network for Salient Object Detection in Optical Remote Sensing Images

Paper recorded by Signals 4 on 2026-08-30 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-08-30 on arXiv · recorded by Signals 4 on 2026-09-01

Category: cs.CV · 计算机视觉 · first seen 2026-09-01

Abstract

Salient object detection in optical remote sensing images (ORSI-SOD) requires dense predictions that preserve object completeness and structural continuity under complex backgrounds, scale variation, and irregular object shapes. Existing methods often localize salient regions, but their predictions may still suffer from structural degradation, including fragmented, incomplete, or locally missing f

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#207 most recent of 237 cs.CV papers we have recorded · ↑ newer: Multi-View Reflective Surface Inspection via Semantic-Saliency Cross-V · ↓ older: See the Change, Keep the Flow: Unsupervised Action Segmentation via Sp
Cite this page: SPLG-Mamba: Structure-Preserving Local-Global Mamba Network for Salient Object Detection in Optical Remote Sensing Images: the #207 most recent of 237 cs.CV papers we have recorded (as of 2026-08-30). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/splg-mamba-structure-preserving-local-global-mamba-network-for-salient-object-de.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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