In the present study, towards reliable and efficient object detection in thermal infrared (TIR)
images, we put forward a novel object detection approach, termed TIRNet, which is built …

The early recognition and understanding of the actions performed by pedestrians in traffic
scenes leads to an anticipation of pedestrian intentions in advance and helps in the process …

Pedestrian detection in thermal infrared images poses unique challenges because of the
low resolution and noisy nature of the image. Here, we propose a mid-level attribute in the …

Lossy image compression strategies allow for more efficient storage and transmission of
data by encoding data to a reduced form. This is essential enable training with larger …

Abstract The Segment Anything Model (SAM) is a deep neural network foundational model
designed to perform instance segmentation which has gained significant popularity given its …

The detection of moving objects is a crucial step for many video surveillance applications
whether using a visible camera (VIS) or an infrared (IR) one. In order to profit from both …

Histogram of oriented gradient (HOG) features in combination with support vector machine
(SVM) classification are still widely reported as a de facto standard benchmark to evaluate …

This paper presents a novel method to detect pedestrians in the far infrared (FIR) domain at
night. In existing infrared data, the brightness is distorted by the contrast of the scene …

Infrared pedestrian detection has important theoretical research value and a wide range of
application scenarios. Because of its special imaging method, infrared images can be used …

Infrared image can show the state of objects at night, which is an important way to obtain the
information of objects at night. To solve the extraction of pedestrians completely from single …