Understanding human behavior and activity facilitates advancement of numerous real-world
applications, and is critical for video analysis. Despite the progress of action recognition …

Temporal action proposal generation is an challenging and promising task which aims to
locate temporal regions in real-world videos where action or event may occur. Current …

Temporal action proposal generation is an important yet challenging problem, since
temporal proposals with rich action content are indispensable for analysing real-world …

Dense video captioning aims to generate text descriptions for all events in an untrimmed
video. This involves both detecting and describing events. Therefore, all previous methods …

Current action recognition methods heavily rely on trimmed videos for model training.
However, it is expensive and time-consuming to acquire a large-scale trimmed video …

With the exponential growth of video data, there is an urgent need for automated technology
to analyze and comprehend video content. However, existing video understanding models …

We address the problem of Temporal Action Proposal (TAP) generation. This is an important
problem, as fast extraction of semantically important (eg human actions) segments from …

Generating multi-sentence descriptions for video is considered to be the most complex task
in computer vision and natural language understanding due to the intricate nature of video …

Abstract Video-Text Retrieval (VTR) aims to search for the most relevant video related to the
semantics in a given sentence, and vice versa. In general, this retrieval task is composed of …

Most modern approaches in temporal action localization divide this problem into two parts:(i)
short-term feature extraction and (ii) long-range temporal boundary localization. Due to the …