Camouflaged object detection (COD) is the challenging task of identifying camouflaged
objects visually blended into surroundings. Albeit achieving remarkable success, existing …

Unpaired medical image enhancement (UMIE) aims to transform a low-quality (LQ) medical
image into a high-quality (HQ) one without relying on paired images for training. While most …

Heterogeneous image fusion (HIF) techniques aim to enhance image quality by merging
complementary information from images captured by different sensors. Among these …

Deep generative models have garnered significant attention in low-level vision tasks due to
their generative capabilities. Among them, diffusion model-based solutions, characterized by …

Traffic sign classification plays a vital role in autonomous vehicles for its powerful capability
in information representation. However, the low-quality data of traffic signs captured by in …

Illumination degradation image restoration (IDIR) techniques aim to improve the visibility of
degraded images and mitigate the adverse effects of deteriorated illumination. Among these …

Infrared and visible data fusion (IVF) aims to generate a fused output that simultaneously
highlights salient thermal radiation features and preserves texture information, which can not …

Camouflaged Object Detection (COD) refers to the task of identifying and segmenting
objects that blend seamlessly into their surroundings, posing a significant challenge for …

Concealed object segmentation (COS) is a challenging task that involves localizing and
segmenting those concealed objects that are visually blended with their surrounding …

Infrared and visible image fusion (IVIF) aims to preserve thermal radiation information from
infrared images while integrating texture details from visible images. Thermal radiation …