Visual grounding, ie, localizing objects in images according to natural language queries, is
an important topic in visual language understanding. The most effective approaches for this …

Understanding videos to localize moments with natural language often requires large
expensive annotated video regions paired with language queries. To eliminate the …

Exploiting the spatial structure in scene images is a key research direction for scene
recognition. Due to the large intra-class structural diversity, building and modeling flexible …

Multi-instance learning (MIL) is able to cope with the weakly supervised problems where the
training data is represented by labeled bags consisting of multiple unlabeled instances. Due …

In machine learning, feature selection is a kind of important dimension reduction techniques,
which aims to choose features with the best discriminant ability to avoid the issue of curse of …

In recent years, with the rapid development of convolutional neural networks (CNNs), a
series of computer vision tasks have been solved. However, scene recognition is still a …

With the rise of deep learning algorithms nowadays, scene image representation methods
have achieved a significant performance boost, particularly in accuracy, in classification …

There have been many methods to improve the capacity of scene classification of service
robots. However, most of them are proposed from a technical standpoint but without …

The goal of few-shot image recognition is to classify different categories with only one or a
few training samples. Previous works of few-shot learning mainly focus on simple images …

Scene classification is a valuable classification subtask and has its own characteristics
which still needs more in-depth studies. Basically, scene characteristics are distributed over …