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 temporal action localization aims to recognize and localize action
segments in untrimmed videos given only video-level action labels for training. Without the …

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

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

We study on weakly-supervised object detection (WSOD) which plays a vital role in relieving
human involvement from object-level annotations. Predominant works integrate region …

Weakly supervised anomaly detection (WSAD) is a challenging task with only normal and
anomaly video label supervision but required to localize intervals where anomalies take …

Despite significant efforts made so far for Weakly Supervised Object Detection (WSOD),
proposal generation and proposal selection are still two major challenges. In this paper, we …

It is challenging for weakly supervised object detection network to precisely predict the
positions of the objects, since there are no instance-level category annotations. Most …

Object detection, aiming at locating objects from a large number of specific categories in
natural images, is a fundamental but challenging task in the field of computer vision. Recent …

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