Robust and accurate geometric understanding against adverse weather conditions is one
top prioritized conditions to achieve a high-level autonomy of self-driving cars. However …

RGB-thermal semantic segmentation is one potential solution to achieve reliable semantic
scene understanding in adverse weather and lighting conditions. However, the previous …

Multi-target multi-camera tracking is a crucial task that involves identifying and tracking
individuals over time using video streams from multiple cameras. This task has practical …

Over recent years, there has been an increase in research interest regarding depth
estimation using multiple-spectrum images from Visible-Light (VIS) and Thermal-Infrared …

Adding artificial patterns to objects like QR codes can ease tasks such as object tracking
robot navigation and conveying information (eg a label or a website link). However these …

Aerial scene understanding systems face stringent payload restrictions and must often rely
on monocular depth estimation for modeling scene geometry, which is an inherently illposed …

Depth estimation from thermal images is one potential solution to achieve reliability and
robustness against diverse weather, lighting, and environmental conditions. Also, a self …

Predicting depth maps from monocular images has made an impressive performance in the
past years. However, most depth estimation methods are trained with paired image-depth …

Monocular depth estimation (MDE) from thermal images is a crucial technology for robotic
systems operating in challenging conditions such as fog, smoke, and low light. The limited …

Thermal infrared (TIR) cameras are emerging as promising sensors in safety-related fields
due to their robustness against external illumination. However, RAW TIR image has 14 bits …