4 citations · 11 across the 18 of their papers we have counts for
5 papers · 2 filters
Exploring the Underwater World Segmentation without Extra Training
Bingyu Li, Tao Huo, Da Zhang +3
Accurate segmentation of marine organisms is vital for biodiversity monitoring and ecological assessment, yet existing datasets and models remain largely limited to terrestrial sce…
UWBench: A Comprehensive Vision-Language Benchmark for Underwater Understanding
Da Zhang, Chenggang Rong, Bingyu Li +4
Large vision-language models (VLMs) have achieved remarkable success in natural scene understanding, yet their application to underwater environments remains largely unexplored. Un…
MARIS: Marine Open-Vocabulary Instance Segmentation with Geometric Enhancement and Semantic Alignment
Bingyu Li, Feiyu Wang, Da Zhang +3
Most existing underwater instance segmentation approaches are constrained by close-vocabulary prediction, limiting their ability to recognize novel marine categories. To support ev…
Exploring Efficient Open-Vocabulary Segmentation in the Remote Sensing
Bingyu Li, Haocheng Dong, Da Zhang +3
Open-Vocabulary Remote Sensing Image Segmentation (OVRSIS), an emerging task that adapts Open-Vocabulary Segmentation (OVS) to the remote sensing (RS) domain, remains underexplored…
FGAseg: Fine-Grained Pixel-Text Alignment for Open-Vocabulary Semantic Segmentation
Bingyu Li, Da Zhang, Zhiyuan Zhao +2
Open-vocabulary segmentation aims to identify and segment specific regions and objects based on text-based descriptions. A common solution is to leverage powerful vision-language m…