375 citations · 431 across the 13 of their papers we have counts for
13 papers
Mamba: CLIP-driven Mamba Model for Multi-modal Remote Sensing Classification
Mingxiang Cao, Weiying Xie, Xin Zhang +4
Multi-modal fusion holds great promise for integrating information from different modalities. However, due to a lack of consideration for modal consistency, existing multi-modal fu…
DiffCLIP: Few-shot Language-driven Multimodal Classifier
Jiaqing Zhang, Mingxiang Cao, Xue Yang +2
Visual language models like Contrastive Language-Image Pretraining (CLIP) have shown impressive performance in analyzing natural images with language information. However, these mo…
SeaDATE: Remedy Dual-Attention Transformer with Semantic Alignment via Contrast Learning for Multimodal Object Detection
Shuhan Dong, Yunsong Li, Weiying Xie +4
Multimodal object detection leverages diverse modal information to enhance the accuracy and robustness of detectors. By learning long-term dependencies, Transformer can effectively…
FoRA: Low-Rank Adaptation Model beyond Multimodal Siamese Network
Weiying Xie, Yusi Zhang, Tianlin Hui +3
Multimodal object detection offers a promising prospect to facilitate robust detection in various visual conditions. However, existing two-stream backbone networks are challenged b…
Hyperspectral Anomaly Detection with Self-Supervised Anomaly Prior
Yidan Liu, Weiying Xie, Kai Jiang +3
The majority of existing hyperspectral anomaly detection (HAD) methods use the low-rank representation (LRR) model to separate the background and anomaly components, where the anom…
E2E-MFD: Towards End-to-End Synchronous Multimodal Fusion Detection
Jiaqing Zhang, Mingxiang Cao, Weiying Xie +5
Multimodal image fusion and object detection are crucial for autonomous driving. While current methods have advanced the fusion of texture details and semantic information, their c…
Multimodal Informative ViT: Information Aggregation and Distribution for Hyperspectral and LiDAR Classification
Jiaqing Zhang, Jie Lei, Weiying Xie +3
In multimodal land cover classification (MLCC), a common challenge is the redundancy in data distribution, where irrelevant information from multiple modalities can hinder the effe…
SwiMDiff: Scene-wide Matching Contrastive Learning with Diffusion Constraint for Remote Sensing Image
Jiayuan Tian, Jie Lei, Jiaqing Zhang +2
With recent advancements in aerospace technology, the volume of unlabeled remote sensing image (RSI) data has increased dramatically. Effectively leveraging this data through self-…
Distribution-aware Interactive Attention Network and Large-scale Cloud Recognition Benchmark on FY-4A Satellite Image
Jiaqing Zhang, Jie Lei, Weiying Xie +3
Accurate cloud recognition and warning are crucial for various applications, including in-flight support, weather forecasting, and climate research. However, recent deep learning a…
Multi-scale direction-aware SAR object detection network via global information fusion
Mingxiang Cao, Weiying Xie, Jie Lei +3
Deep learning has driven significant progress in object detection using Synthetic Aperture Radar (SAR) imagery. Existing methods, while achieving promising results, often struggle…
MDFL: Multi-domain Diffusion-driven Feature Learning
Daixun Li, Weiying Xie, Jiaqing Zhang +1
High-dimensional images, known for their rich semantic information, are widely applied in remote sensing and other fields. The spatial information in these images reflects the obje…
Guided Hybrid Quantization for Object detection in Multimodal Remote Sensing Imagery via One-to-one Self-teaching
Jiaqing Zhang, Jie Lei, Weiying Xie +2
Considering the computation complexity, we propose a Guided Hybrid Quantization with One-to-one Self-Teaching (GHOST}) framework. More concretely, we first design a structure calle…
SuperYOLO: Super Resolution Assisted Object Detection in Multimodal Remote Sensing Imagery
Jiaqing Zhang, Jie Lei, Weiying Xie +3
Accurately and timely detecting multiscale small objects that contain tens of pixels from remote sensing images (RSI) remains challenging. Most of the existing solutions primarily…