Dense video captioning is a task of localizing interesting events from an untrimmed video
and producing textual description (captions) for each localized event. Most of the previous …

Dense video captioning aims to localize and describe important events in untrimmed videos.
Existing methods mainly tackle this task by exploiting only visual features, while completely …

Multi-modal learning, particularly among imaging and linguistic modalities, has made
amazing strides in many high-level fundamental visual understanding problems, ranging …

It is well believed that video captioning is a fundamental but challenging task in both
computer vision and artificial intelligence fields. The prevalent approach is to map an input …

Adversarial susceptibility of neural image captioning is still under-explored due to the
complex multi-model nature of the task. We introduce a GAN-based adversarial attack to …

Audio-visual text generation aims to understand multi-modality contents and translate them
into texts. Although various transfer learning techniques of text generation have been …

Recently, the revival of the semantic similarity concept has been featured by the rapidly
growing artificial intelligence research fueled by advanced deep learning architectures …

Dense captioning methods generally detect events in videos first and then generate
captions for the individual events. Events are localized solely based on the visual cues while …

The video captioning task aims to describe video content using several natural-language
sentences. Although one-step encoder-decoder models have achieved promising progress …

TV show captioning aims to generate a linguistic sentence based on the video and its
associated subtitle. Compared to purely video-based captioning, the subtitle can provide the …