Abstract: One of the main challenges in LiDAR-based 3D object detection is that the sensors often fail to capture the complete spatial information about the objects due to long distance and occlusion.
Abstract: With the rapidly increasing demand for oriented object detection (OOD), recent research involving weakly-supervised detectors for learning OOD from point annotations has gained great ...
Abstract: With the rapidly increasing demand for oriented object detection (OOD), recent research involving weakly-supervised detectors for learning rotated box (RBox) from the horizontal box (HBox) ...
In this article, we will be sharing some free Python programming courses offered by SWAYAM, MIT and Google that can be great ...
Abstract: Accurately estimating the orientation of visual objects with compact rotated bounding boxes (RBoxes) has become a prominent demand, which challenges existing object detection paradigms that ...
Abstract: Vehicle detection is vital for urban planning and traffic management. Optical remote sensing imagery, known for its high resolution and extensive coverage, is ideal for this task.
Abstract: Oriented object detection has gained increasing attention due to its ability to detect objects with arbitrary orientations in the field of remote sensing (RS) images. However, the laborious ...
Abstract: Weakly textured objects are frequently manipulated by industrial and domestic robots, and the most common two types are transparent and reflective objects; however, their unique visual ...
Abstract: Aiming at the current object classification algorithm based on the original point cloud's insufficient ability to extract local geometric features, this thesis proposes a point cloud object ...
Abstract: LiDAR-based 3D single object tracking has received remarkable attention due to its crucial role in robotics and autonomous driving. Most of them are based on hierarchical feature structures ...
Abstract: Object detection in remote sensing is a challenging task due to the arbitrary orientations of objects and the vast variation in the number of objects within a single image. For instance, one ...
Abstract: Recently, many lightweight neural networks have been deployed on airborne or satellite remote sensing platforms for real-time object detection. To bridge the performance gap between ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback