Current object detectors are limited in vocabulary size due to the small scale of detection
datasets. Image classifiers, on the other hand, reason about much larger vocabularies, as …

Existing open-vocabulary object detectors typically enlarge their vocabulary sizes by
leveraging different forms of weak supervision. This helps generalize to novel objects at …

目标检测是计算机视觉领域中最基础且最重要的任务之一, 是行为识别与人机交互等高层视觉
任务的基础. 随着深度学习技术的发展, 目标检测模型的准确率和效率得到了大幅提升 …

The goal of open-vocabulary detection is to identify novel objects based on arbitrary textual
descriptions. In this paper, we address open-vocabulary 3D point-cloud detection by a …

Weakly supervised learning has emerged as a compelling tool for object detection by
reducing the need for strong supervision during training. However, major challenges …

Abstract Weakly Supervised Object Detection (WSOD) has emerged as an effective tool to
train object detectors using only the image-level category labels. However, without object …

In recent years, weakly supervised object detection has attracted great attention in the
computer vision community. Although numerous deep learning-based approaches have …

Weakly supervised object detection (WSOD) has received widespread attention since it
requires only image-category annotations for detector training. Many advanced approaches …

The use of robotic systems on construction sites can efficiently reduce construction time and
increase safety by replacing construction workers in monotonous or dangerous operations …

Weakly supervised object localization (WSOL) aims to localize object with only weak
supervision like image-level labels. However, a long-standing problem for available …