Object detection is a challenging computer vision task with numerous real-world applications. In recent years, the concept of object relationship model has become helpful for and been verified realized in deep learning. Nonetheless, most approaches to modeling relations are limited using anchor-based algorithms; they cannot be directly migrated anchor-free frameworks. The reason that algorithms...

Abstract Salient object detection via deep neural networks usually needs a large amount of images with human annotation. To avoid laborious and consuming annotation, we propose robust unsupervised salient method three stages in this work. Our first uses unlabeled data to generate an activation map which indicates the coarse location object. Then one scribble generation based on is proposed, pro...

The 3D object detection is the key issue in autonomous driving system. This particularly challenging when only relies on a single perspective camera. anchor-free and keypoint-based models receive increasing attention recently due to their effectiveness simplicity. However, most of these methods are vulnerable occlusion truncation objects. In this paper, single-stage monocular model proposed. An...