7 accepted papers
Open-vocabulary segmentation enables pixel-level recognition from an open set of textual categories, allowing generalization beyond fixed classes. Despite great potential in remote sensing, progress in this area remains largely limited to clear-sky optical data and struggles under cloudy or haze-con
Large vision-language models (VLMs) have made great achievements in Earth vision. However, complex disaster scenes with diverse disaster types, geographic regions, and satellite sensors have posed new challenges for VLM applications. To fill this gap, we curate the first remote sensing vision-langua…
Multimodal large language models (MLLMs) have demonstrated remarkable capabilities in visual understanding, but their application to long-term Earth observation analysis remains limited, primarily focusing on single-temporal or bi-temporal imagery. To address this gap, we introduce **DVL-Suite**, a…
Global semantic 3D understanding from single-view high-resolution remote sensing (RS) imagery is crucial for Earth observation (EO). However, this task faces significant challenges due to the high costs of annotations and data collection, as well as geographically restricted data availability. To ad…
In this work, a novel deep rotation forest is proposed to fuse hyperspectral (HS) and LiDAR. First, we extract the spatial and elevation information of two datasets by using morphological filters. Then, each feature source is applied to superpixel segmentation and then are treated as the input of de…
Due to the benefits and limitation of different remote sensing sensors, fusion of the features from multiple sensors, such as hyperspectral and light detection and ranging (LiDAR) is an effective method for land cover mapping. In this paper, we propose a novel ensemble classifier to fuse hyperspectr…
Conventional feature extraction methods cannot fully exploit both the spectral and spatial information of hyperspectral imagery. In this paper, we propose an ensemble method of subspace independent component analysis (ICA) and edge-preserving filtering (EPF) for the classification of hyper-spectral…