Mitigate Target-level Insensitivity of Infrared Small Target Detection via Posterior Distribution Modeling
The author proposes a diffusion model framework for Infrared Small Target Detection to address target-level insensitivity by generating mask posterior distributions.
IRSTD-Diff: Generative Approach for Infrared Small Target Detection
Proposing a diffusion model framework for IRSTD to address target-level insensitivity and designing a low-frequency isolation module in the wavelet domain.
Enhancing Infrared Small Target Detection with Scale and Location Sensitivity
A novel Scale and Location Sensitive (SLS) loss is proposed to improve infrared small target detection by addressing the limitations of existing loss functions in capturing scale and location information. A simple Multi-Scale Head is introduced to the plain U-Net (MSHNet) to leverage the SLS loss, achieving state-of-the-art performance without complex model structures.
Spatial-channel Cross Transformer Network for Accurate Infrared Small Target Detection
The proposed Spatial-channel Cross Transformer Network (SCTransNet) leverages spatial-channel cross transformer blocks to effectively model the semantic differences between infrared small targets and complex backgrounds, enabling accurate detection of small targets.
Gradient-Based Attention Fusion for Efficient Infrared Small Target Detection
The proposed Gradient Attention Network (GaNet) effectively extracts and preserves edge and gradient information of small infrared targets, while a global feature extraction module provides comprehensive background perception to improve detection performance.
