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

Object detection in optical remote sensing images, being a fundamental but challenging
problem in the field of aerial and satellite image analysis, plays an important role for a wide …

In this work, we propose Adversarial Complementary Learning (ACoL) to automatically
localize integral objects of semantic interest with weak supervision. We first mathematically …

Object detection, including objectness detection (OD), salient object detection (SOD), and
category-specific object detection (COD), is one of the most fundamental yet challenging …

Weakly supervised learning of object detection is an important problem in image
understanding that still does not have a satisfactory solution. In this paper, we address this …

Weakly supervised object localization (WSOL) is a challenging problem when given image
category labels but requires to learn object localization models. Optimizing a convolutional …

The abundant spatial and contextual information provided by the advanced remote sensing
technology has facilitated subsequent automatic interpretation of the optical remote sensing …

Weakly Supervised Object Detection (WSOD), using only image-level annotations to train
object detectors, is of growing importance in object recognition. In this paper, we propose a …

Of late, weakly supervised object detection is with great importance in object recognition.
Based on deep learning, weakly supervised detectors have achieved many promising …

Weakly-supervised object localization (WSOL) has gained popularity over the last years for
its promise to train localization models with only image-level labels. Since the seminal …