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Beyond Weak Labels: Prompt-Guided Local Refinement for Weakly Supervised Water Segmentation in High-Resolution Multispectral Imagery

Paper recorded by Signals 4 on 2026-09-09 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-09 on arXiv · recorded by Signals 4 on 2026-09-10

Category: cs.CV · 计算机视觉 · first seen 2026-09-10

Abstract

High-resolution water mapping supports environmental monitoring and related applications, but accurate pixel-level labels are difficult and costly to produce. Official hydrographic vectors provide scalable weak supervision, but they contain artifacts like boundary noise, temporal mismatch, and omissions of small water structures. We propose a two-stage framework for weakly supervised water segment

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#108 most recent of 237 cs.CV papers we have recorded · ↑ newer: Shape-guided Gaussian Splatting for Sparse-View X-ray 3D Reconstructio · ↓ older: AVSRBench: A Multi-Condition AVSR Benchmark
Cite this page: Beyond Weak Labels: Prompt-Guided Local Refinement for Weakly Supervised Water Segmentation in High-Resolution Multispectral Imagery: the #108 most recent of 237 cs.CV papers we have recorded (as of 2026-09-09). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/beyond-weak-labels-prompt-guided-local-refinement-for-weakly-supervised-water-se.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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