Abstract Machine learning has become the state-of-the-art technique for many tasks
including computer vision, natural language processing, speech processing tasks, etc …

Object Detection is the task of classification and localization of objects in an image or video.
It has gained prominence in recent years due to its widespread applications. This article …

In this work, we present SEEM, a promotable and interactive model for segmenting
everything everywhere all at once in an image. In SEEM, we propose a novel and versatile …

In this work, we present OpenSeeD, a simple Open-vocabulary Segmentation and Detection
framework that learns from different segmentation and detection datasets. To bridge the gap …

With the rise of deep convolutional neural networks, object detection has achieved
prominent advances in past years. However, such prosperity could not camouflage the …

The complex nature of combining localization and classification in object detection has
resulted in the flourished development of methods. Previous works tried to improve the …

UAV multitarget detection plays a pivotal role in civil and military fields. Although deep
learning methods provide a more effective solution to this task, changes in target size, shape …

Recent outstanding results of supervised object detection in competitions and challenges
are often associated with specific metrics and datasets. The evaluation of such methods …

目标检测是计算机视觉领域的一个基础任务和研究热点. YOLO 将目标检测概括为一个回归问题
, 实现端到端的训练和检测, 由于其良好的速度-精度平衡, 近几年一直处于目标检测领域的领先 …

In this paper, we introduce Semantic-SAM, a universal image segmentation model to enable
segment and recognize anything at any desired granularity. Our model offers two key …