From the 1 of 6 linked papers with an AI index.
6 papers
Think with Extra-Image: A Farmland Segmentation Agent Driven by Spatio-Temporal Information Gain
Haiyang Wu, Weiliang Mu, Zhuofei Du +4
The paper introduces FarmSeeker, a dynamic segmentation agent that detects ambiguous farmland regions in remote sensing images and queries additional spatio‑temporal data to improv…
Feasibility of Indoor Frame-Wise Lidar Semantic Segmentation via Distillation from Visual Foundation Model
Haiyang Wu, Juan J. Gonzales Torres, George Vosselman +1
Frame-wise semantic segmentation of indoor lidar scans is a fundamental step toward higher-level 3D scene understanding and mapping applications. However, acquiring frame-wise grou…
FarmMind: Reasoning-Query-Driven Dynamic Segmentation for Farmland Remote Sensing Images
Haiyang Wu, Weiliang Mu, Jipeng Zhang +4
Existing methods for farmland remote sensing image (FRSI) segmentation generally follow a static segmentation paradigm, where analysis relies solely on the limited information cont…
Remote Sensing Image Intelligent Interpretation with the Language-Centered Perspective: Principles, Methods and Challenges
Haifeng Li, Wang Guo, Haiyang Wu +6
The mainstream paradigm of remote sensing image interpretation has long been dominated by vision-centered models, which rely on visual features for semantic understanding. However,…
A Joint Learning Framework with Feature Reconstruction and Prediction for Incomplete Satellite Image Time Series in Agricultural Semantic Segmentation
Yuze Wang, Mariana Belgiu, Haiyang Wu +3
Satellite Image Time Series (SITS) is crucial for agricultural semantic segmentation. However, Cloud contamination introduces time gaps in SITS, disrupting temporal dependencies an…
A large-scale image-text dataset benchmark for farmland segmentation
Chao Tao, Dandan Zhong, Weiliang Mu +2
The traditional deep learning paradigm that solely relies on labeled data has limitations in representing the spatial relationships between farmland elements and the surrounding en…