In this paper, we present a one-stage framework TriDet for temporal action detection.
Existing methods often suffer from imprecise boundary predictions due to the ambiguous …

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) aims to identify the action boundaries and the
corresponding category within untrimmed videos. Inspired by the success of DETR in object …

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 …

Recently temporal action detection (TAD) has seen significant performance improvement
with end-to-end training. However due to the memory bottleneck only models with limited …

Ultra-high-resolution aerial videos are becoming increasingly popular for enhancing
surveillance capabilities in sparsely populated areas. However analyzing human activities …

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

The temporal action localization research aims to discover action instances from untrimmed
videos, representing a fundamental step in the field of intelligent video understanding. With …

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 …

Recent proposed neural network-based Temporal Action Detection (TAD) models are
inherently limited to extracting the discriminative representations and modeling action …