Insect pest is one of the main causes affecting agricultural crop yield and quality all over the
world. Rapid and reliable insect pest monitoring plays a crucial role in population prediction …

Pedestrian detection has a wide range of application prospects in many fields such as
unmanned driving, intelligent monitoring, robot, etc., and has always been a hot issue in the …

Pedestrian detection is an important but challenging problem in computer vision, especially
in human-centric tasks. Over the past decade, significant improvement has been witnessed …

Hyperspectral remote sensing is well-known for its extraordinary spectral distinguishability to
discriminate different materials. However, the cost of hyperspectral image (HSI) acquisition …

While impressive progress has been achieved, video instance segmentation (VIS) methods
with per-clip input often fail on challenging videos with occluded objects and crowded …

Acquiring incomplete k-space matrices is an effective way to accelerate Magnetic
Resonance Imaging (MRI). It is an important and challenging task to accurately reconstruct …

State-of-the-art pedestrian detectors have performed promisingly on non-occluded
pedestrians, yet they are still confronted by heavy occlusions. Although many previous …

Pedestrian detection relying on deep convolution neural networks has made significant
progress. Though promising results have been achieved on standard pedestrians, the …

To achieve accurate and robust object detection in the real-world scenario, various forms of
images are incorporated, such as color, thermal, and depth. However, multimodal data often …

Pedestrian detection is an important branch of computer vision, and has important
applications in the fields of autonomous driving, artificial intelligence and video surveillance …