24 citations · 28 across the 6 of their papers we have counts for
6 papers
ProtoRAG: Prototype-Based Retrieval Augmentation for Few-Shot Fine-Grained Remote Sensing Object Detection
Jian Wang, Yuxiang Hong, Chufeng Zhou +2
Few-shot fine-grained object detection (FGOD) in remote sensing imagery is challenging because limited annotations must support both object localization and discrimination among vi…
Real-World Knowledge-Guided Change Data Synthesis for Remote Sensing
Yaoyi Qi, Xingxing Weng, Chao Pang +5
Change data synthesis provides a cost-effective solution for expanding training data and improving the performance of change detection models. However, existing synthesis methods t…
Continual Vision-Language Learning for Remote Sensing: Benchmarking and Analysis
Xingxing Weng, Ruifeng Ni, Chao Pang +5
Current remote sensing vision-language models (RS VLMs) demonstrate impressive performance in image interpretation but rely on static training data, limiting their ability to accom…
DragOSM: Extract Building Roofs and Footprints from Aerial Images by Aligning Historical Labels
Kai Li, Xingxing Weng, Yupeng Deng +4
Extracting polygonal roofs and footprints from remote sensing images is critical for large-scale urban analysis. Most existing methods rely on segmentation-based models that assume…
Vision-Language Modeling Meets Remote Sensing: Models, Datasets and Perspectives
Xingxing Weng, Chao Pang, Gui-Song Xia
Vision-language modeling (VLM) aims to bridge the information gap between images and natural language. Under the new paradigm of first pre-training on massive image-text pairs and…
VHM: Versatile and Honest Vision Language Model for Remote Sensing Image Analysis
Chao Pang, Xingxing Weng, Jiang Wu +8
This paper develops a Versatile and Honest vision language Model (VHM) for remote sensing image analysis. VHM is built on a large-scale remote sensing image-text dataset with rich-…