In last years, computer vision has shown important advances, mainly using the application of
supervised machine learning (ML) and deep learning (DL) techniques. The objective of this …

Video description is the automatic generation of natural language sentences that describe
the contents of a given video. It has applications in human-robot interaction, hel** the …

Most video captioning models are designed to process short video clips of few seconds and
output text describing low-level visual concepts (eg objects scenes atomic actions). However …

Learning text-video embeddings usually requires a dataset of video clips with manually
provided captions. However, such datasets are expensive and time consuming to create and …

Taking full advantage of the information from both vision and language is critical for the
video captioning task. Existing models lack adequate visual representation due to the …

How do humans recognize the action" opening a book"? We argue that there are two
important cues: modeling temporal shape dynamics and modeling functional relationships …

Video question answering (VideoQA) is challenging as it requires modeling capacity to distill
dynamic visual artifacts and distant relations and to associate them with linguistic concepts …

Video captioning refers to automatic generate natural language sentences, which
summarize the video contents. Inspired by the visual attention mechanism of human beings …

Recently image question answering (ImageQA) has gained lots of attention in the research
community. However, as its natural extension, video question answering (VideoQA) is less …

Recent progress in using long short-term memory (LSTM) for image captioning has
motivated the exploration of their applications for video captioning. By taking a video as a …