activity
20222025
most citedSuperYOLO: Super Resolution Assisted Object Detection in Multimodal Remote Sensing Imagery

375 citations · 431 across the 13 of their papers we have counts for

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13 papers · 1 filter

cs.CV2025

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…

cs.CV2024

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…

cs.CV2024

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…

cs.CV2024

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…

cs.CV2024★ 1 cited

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…

cs.CV2024

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…