The appearance of generative adversarial networks (GAN) provides a new approach and
framework for computer vision. Compared with traditional machine learning algorithms, GAN …

Video moment localization, also known as video moment retrieval, aims to search a target
segment within a video described by a given natural language query. Beyond the task of …

In recent years, graph convolutional neural networks have become research focus and
inspired new ideas for emotion recognition based on EEG. Deep learning has been widely …

Multimodal representation learning, which aims to narrow the heterogeneity gap among
different modalities, plays an indispensable role in the utilization of ubiquitous multimodal …

Recent successes in Generative Adversarial Networks (GAN) have affirmed the importance
of using more data in GAN training. Yet it is expensive to collect data in many domains such …

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

Most of the recent progresses on visual question answering are based on recurrent neural
networks (RNNs) with attention. Despite the success, these models are often timeconsuming …

Recent progress has been made in using attention based encoder-decoder framework for
image and video captioning. Most existing decoders apply the attention mechanism to every …

Hashing methods have been extensively applied to efficient multimedia data indexing and
retrieval on account of the explosion of multimedia data. Cross-modal hashing usually …

Video captioning aims to automatically generate natural language descriptions of video
content, which has drawn a lot of attention recent years. Generating accurate and fine …