Detecting objects in large-scale drone-view images is notoriously challenging due to their
uneven distribution and scale variation caused by photoing angles. Common approaches …

Image and video analysis requires not only accurate object but also the understanding of
relationships among detected objects. Common solutions to relation modeling typically …

In recent research significant attention has been devoted to the open-vocabulary object
detection task aiming to generalize beyond the limited number of classes labeled during …

Artificial intelligence models play a crucial role in monitoring and maintaining railroad
infrastructure by analyzing image data of foreign objects on power transmission lines …

The hybrid deep models of Vision Transformer (ViT) and Convolution Neural Network (CNN)
have emerged as a powerful class of backbones for vision tasks. Scaling up the input …

Autonomous driving, as a pivotal technology in modern transportation, is progressively
transforming the modalities of human mobility. In this domain, vehicle detection is a …

Video instance segmentation on mobile devices is an important yet very challenging edge AI
problem. It mainly suffers from (1) heavy computation and memory costs for frame-by-frame …

Transformer-based instance-level recognition has attracted increasing research attention
recently due to the superior performance. However, although attempts have been made to …

Compared to the remarkable progress within the discipline of object detection in recent
years, real-time detection of non-salient objects remains a challenging research task …

Camera traps are widely used for wildlife monitoring and making informed conservation and
land-management decisions, but the resulting 'big data'are laborious to process. Deep …