Accelerated by the tremendous increase in Internet bandwidth and storage space, video data has been generated, published and spread explosively, becoming an indispensable part of today's big data. In this paper, we focus on reviewing two lines of research aiming to stimulate the comprehension of videos with deep learning: video classification and video captioning. While video classification con...

In video captioning task, the best practice has been achieved by attention-based models which associate salient visual components with sentences in the video. However, existing study follows a common procedure which includes a frame-level appearance modeling and motion modeling on equal interval frame sampling, which may bring about redundant visual information, sensitivity to content noise and...

Manual image annotation is a major bottleneck in the processing of medical images and the accuracy of these reports varies depending on the clinician’s expertise. Automating some or all of the processes would have enormous impact in terms of efficiency, cost and accuracy. Previous approaches to automatically generating captions from images have relied on hand-crafted pipelines of feature extrac...

Image captioning has emerged as an interesting research field in recent years due to its broad application scenarios. The traditional paradigm of image relies on paired image-caption datasets train the model a supervised manner. However, creating such for every target language is prohibitively expensive, which hinders extensibility technology and deprives large part world population benefit. In...

In the past few years, neural networks have fueled dramatic advances in image classi cation. Emboldened, researchers are looking for more challenging applications for computer vision and arti cial intelligence systems. They seek not only to assign numerical labels to input data, but to describe the world in human terms. Image and video captioning is among the most popular applications in this t...

Image captioning implies automatically generating textual descriptions of images based only on the visual input. Although this has been an extensively addressed research topic in recent years, not many contributions have made domain art historical data. In particular context, task image is confronted with various challenges such as lack large-scale datasets image-text pairs, complexity meaning ...