Guided depth map super-resolution (GDSR), which aims to reconstruct a high-resolution
depth map from a low-resolution observation with the help of a paired high-resolution color …

Guided depth map super-resolution (GDSR), as a hot topic in multi-modal image processing,
aims to upsample low-resolution (LR) depth maps with additional information involved in …

Integrating an RGB camera into a ToF imaging system has become a significant technique
for perceiving the real world. The RGB guided ToF imaging system is crucial to several …

Many low-level vision tasks, including guided depth super-resolution (GDSR), struggle with
the issue of insufficient paired training data. Self-supervised learning is a promising solution …

Multimodal face anti-spoofing systems adopt multiple sensor modalities, such as infrared,
color, depth, and thermal, to distinguish between living and spoofing faces via …

Details related to tiny abnormal pathologies and textures are crucial for clinical experts and
computer-aided diagnosis in medical imaging. Super-resolving medical images provide …

When traditional super-resolution reconstruction methods are applied to infrared thermal
images, they often ignore the problem of poor image quality caused by the imaging …

Understanding the informative structures of scenes is essential for low-level vision tasks.
Unfortunately, it is difficult to obtain a concrete visual definition of the informative structures …

RGB-guided depth map super-resolution (GDSR) is a pivotal multimodal fusion task aimed
at enhancing low-resolution (LR) depth maps using corresponding high-resolution (HR) …

Due to the limitations and costs of thermal sensors, unmanned aerial vehicle (UAV)
platforms often equip with high-resolution (HR) visible imaging and low-resolution (LR) …