collaborators

9 papers

cs.CV2025

Coupled Degradation Modeling and Fusion: A VLM-Guided Degradation-Coupled Network for Degradation-Aware Infrared and Visible Image Fusion

Tianpei Zhang, Jufeng Zhao, Yiming Zhu +1

Existing Infrared and Visible Image Fusion (IVIF) methods typically assume high-quality inputs. However, when handing degraded images, these methods heavily rely on manually switch…

cs.CV2025

Dual-Domain Perspective on Degradation-Aware Fusion: A VLM-Guided Robust Infrared and Visible Image Fusion Framework

Tianpei Zhang, Jufeng Zhao, Yiming Zhu +1

Most existing infrared-visible image fusion (IVIF) methods assume high-quality inputs, and therefore struggle to handle dual-source degraded scenarios, typically requiring manual s…

eess.IV2025

SWAN: Synergistic Wavelet-Attention Network for Infrared Small Target Detection

Yuxin Jing, Jufeng Zhao, Tianpei Zhang +1

Infrared small target detection (IRSTD) is thus critical in both civilian and military applications. This study addresses the challenge of precisely IRSTD in complex backgrounds. R…

cs.CV2025

FSATFusion: Frequency-Spatial Attention Transformer for Infrared and Visible Image Fusion

Tianpei Zhang, Jufeng Zhao, Yiming Zhu +2

The infrared and visible images fusion (IVIF) is receiving increasing attention from both the research community and industry due to its excellent results in downstream application…

cs.CV2025

WIFE-Fusion:Wavelet-aware Intra-inter Frequency Enhancement for Multi-model Image Fusion

Tianpei Zhang, Jufeng Zhao, Yiming Zhu +1

Multimodal image fusion effectively aggregates information from diverse modalities, with fused images playing a crucial role in vision systems. However, existing methods often negl…

eess.IV2025

Selective Variable Convolution Meets Dynamic Content-Guided Attention for Infrared Small Target Detection

Yirui Chen, Yiming Zhu, Yuxin Jing +2

Infrared Small Target Detection (IRSTD) system aims to identify small targets in complex backgrounds. Due to the convolution operation in Convolutional Neural Networks (CNNs), appl…