Image-based visual-language (I-VL) pre-training has shown great success for learning joint
visual-textual representations from large-scale web data, revealing remarkable ability for …

Abstract Temporal Action Detection (TAD) aims to accurately capture each action interval in
an untrimmed video and to understand human actions. This paper comprehensively surveys …

Abstract Temporal Action Detection (TAD) is challenging but fundamental for real-world
video applications. Recently, DETR-based models have been devised for TAD but have not …

We propose a new formulation of temporal action detection (TAD) with denoising diffusion,
DiffTAD in short. Taking as input random temporal proposals, it can yield action proposals …

Temporal action detection aims to predict the time intervals and the classes of action
instances in the video. Despite the promising performance, existing two-stream models …

The distribution of total soil nitrogen (TSN) and total soil phosphorus (TSP) plays a pivotal
role in shaping soil quality, fertility, agricultural practices, and environmental balance …

Weakly-supervised temporal action localization (WTAL) learns to detect and classify action
instances with only category labels. Most methods widely adopt the off-the-shelf …

This article studies the multimedia problem of temporal sentence grounding (TSG), which
aims to accurately determine the specific video segment in an untrimmed video according to …

Temporal action localization (TAL), which involves recognizing and locating action
instances, is a challenging task in video understanding. Most existing approaches directly …

Abstract Semi-Supervised Temporal Action Localization (SS-TAL) aims to improve the
generalization ability of action detectors with large-scale unlabeled videos. Albeit the recent …