5 papers
FUSE-RSVLM: Feature Fusion Vision-Language Model for Remote Sensing
Yunkai Dang, Donghao Wang, Jiacheng Yang +7
Large vision-language models (VLMs) exhibit strong performance across various tasks. However, these VLMs encounter significant challenges when applied to the remote sensing domain…
A Benchmark for Ultra-High-Resolution Remote Sensing MLLMs
Yunkai Dang, Meiyi Zhu, Donghao Wang +7
Multimodal large language models (MLLMs) demonstrate strong perception and reasoning performance on existing remote sensing (RS) benchmarks. However, most prior benchmarks rely on…
SEA: Semantic Map Prediction for Active Exploration of Uncertain Areas
Hongyu Ding, Xinyue Liang, Yudong Fang +7
In this paper, we propose SEA, a novel approach for active robot exploration through semantic map prediction and a reinforcement learning-based hierarchical exploration policy. Unl…
Adapting In-Domain Few-Shot Segmentation to New Domains without Source Domain Retraining
Qi Fan, Kaiqi Liu, Nian Liu +4
Cross-domain few-shot segmentation (CD-FSS) aims to segment objects of novel classes in new domains, which is often challenging due to the diverse characteristics of target domains…
Robust Dataset Distillation by Matching Adversarial Trajectories
Wei Lai, Tianyu Ding, ren dongdong +4
Dataset distillation synthesizes compact datasets that enable models to achieve performance comparable to training on the original large-scale datasets. However, existing distillat…