Detecting objects remains one of computer vision and image understanding applications'
most fundamental and challenging aspects. Significant advances in object detection have …

Computer vision is becoming an increasingly trendy word in the area of image processing.
With the emergence of computer vision applications, there is a significant demand to …

Detecting arbitrarily oriented tiny objects poses intense challenges to existing detectors,
especially for label assignment. Despite the exploration of adaptive label assignment in …

Large-scale pre-trained models (PTMs) such as BERT and GPT have recently achieved
great success and become a milestone in the field of artificial intelligence (AI). Owing to …

Tiny object detection (TOD) in aerial images is challenging since a tiny object only contains
a few pixels. State-of-the-art object detectors do not provide satisfactory results on tiny …

Complicated underwater environments bring new challenges to object detection, such as
unbalanced light conditions, low contrast, occlusion, and mimicry of aquatic organisms …

Deep learning-based object detection and instance segmentation have achieved
unprecedented progress. In this article, we propose complete-IoU (CIoU) loss and Cluster …

Object detection or localization is an incremental step in progression from coarse to fine
digital image inference. It not only provides the classes of the image objects, but also …

Three-dimensional object detection from light detection and ranging (LiDAR) point clouds
has gained great attention in recent years due to its wide applications in smart cities and …

In this paper, we propose an anchor-free single-stage LiDAR-based 3D object detector--
RangeDet. The most notable difference with previous works is that our method is purely …