Multimedia retrieval plays an indispensable role in big data utilization. Past efforts mainly
focused on single-media retrieval. However, the requirements of users are highly flexible …

Artificial intelligence systems are increasingly being used in industrial applications, security
and military contexts, disaster response complexes, policing and justice practices, finance …

In this paper, we present an algorithm to directly restore a clear image from a hazy image.
This problem is highly ill-posed and most existing algorithms often use hand-crafted …

This article aims to tackle the problem of group activity recognition in the multiple-person
scene. To model the group activity with multiple persons, most long short-term memory …

Hashing has been widely investigated for large-scale image retrieval due to its search
effectiveness and computation efficiency. In this work, we propose a novel Semantic Guided …

Objects in unmanned aerial vehicle (UAV) images are generally small due to the high-
photography altitude. Although many efforts have been made in object detection, how to …

In this paper, we propose a general dual convolutional neural network (DualCNN) for low-
level vision problems, eg, super-resolution, edge-preserving filtering, deraining and …

Recent years have witnessed meaningful progress in the task of few-shot object detection.
However, most of the existing models are not capable of incremental learning with a few …

Recent works have shown that convolutional neural networks (CNNs) are parameter
redundant, which limits the application of CNNs in Mobile devices with limited memory and …

The convolutional neural network (CNN)-based multi-focus image fusion methods which
learn the focus map from the source images have greatly enhanced fusion performance …