As an emerging and challenging problem in the computer vision community, weakly
supervised object localization and detection plays an important role for develo** new …

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

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

Object detection using single point supervision has received increasing attention over the
years. However, the performance gap between point supervised object detection (PSOD) …

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

Weakly supervised object detection in remote sensing images (RSI) is still a challenge
because of the lack of instance-level labels, and many existing methods have two problems …

Abstract Weakly-Supervised Object Detection (WSOD) and Localization (WSOL), ie.,
detecting multiple and single instances with bounding boxes in an image using image-level …

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

Abstract Dense Event Captioning (DEC) aims to jointly localize and describe multiple events
of interest in untrimmed videos, which is an advancement of the conventional video …

Object detection (OD), a crucial vision task, remains challenged by the lack of large training
datasets with precise object localization labels. In this work, we propose ALWOD, a new …