75 citations · 111 across the 7 of their papers we have counts for
7 papers
Seeking Consensus: Geometric-Semantic On-the-Fly Recalibration for Open-Vocabulary Remote Sensing Semantic Segmentation
Guanchun Wang, Chenxiao Wu, Xiangrong Zhang +4
Open-vocabulary semantic segmentation (OVSS) in remote sensing images is a promising task that employs textual descriptions for identifying undefined land cover categories. Despite…
ACMamba: Fast Unsupervised Anomaly Detection via An Asymmetrical Consensus State Space Model
Guanchun Wang, Xiangrong Zhang, Yifei Zhang +4
Unsupervised anomaly detection in hyperspectral images (HSI), aiming to detect unknown targets from backgrounds, is challenging for earth surface monitoring. However, current studi…
SMamba: A Spatial-spectral State Space Model for Hyperspectral Image Classification
Guanchun Wang, Xiangrong Zhang, Zelin Peng +2
Land cover analysis using hyperspectral images (HSI) remains an open problem due to their low spatial resolution and complex spectral information. Recent studies are primarily dedi…
Remote Sensing Object Detection Meets Deep Learning: A Meta-review of Challenges and Advances
Xiangrong Zhang, Tianyang Zhang, Guanchun Wang +4
Remote sensing object detection (RSOD), one of the most fundamental and challenging tasks in the remote sensing field, has received longstanding attention. In recent years, deep le…
DiffUCD:Unsupervised Hyperspectral Image Change Detection with Semantic Correlation Diffusion Model
Xiangrong Zhang, Shunli Tian, Guanchun Wang +2
Hyperspectral image change detection (HSI-CD) has emerged as a crucial research area in remote sensing due to its ability to detect subtle changes on the earth's surface. Recently,…
USAGE: A Unified Seed Area Generation Paradigm for Weakly Supervised Semantic Segmentation
Zelin Peng, Guanchun Wang, Lingxi Xie +3
Seed area generation is usually the starting point of weakly supervised semantic segmentation (WSSS). Computing the Class Activation Map (CAM) from a multi-label classification net…
Absolute Wrong Makes Better: Boosting Weakly Supervised Object Detection via Negative Deterministic Information
Guanchun Wang, Xiangrong Zhang, Zelin Peng +3
Weakly supervised object detection (WSOD) is a challenging task, in which image-level labels (e.g., categories of the instances in the whole image) are used to train an object dete…