9 datasets found

Temporal grounding of activities, the identification of specific time intervals of actions within a larger event context, is a critical task in video understanding.

Temporal Action Localization (TAL) in few-shot learning. Our work addresses the inherent limitations of conventional single-prompt learning methods that often lead to...

The dataset used in the paper is ActivityNet, MSR-VTT, and MSVD. The authors used these datasets for text-to-video retrieval tasks.

A dataset for video understanding, containing images and videos.

A dataset for video understanding, containing images and videos.

Visual Semantic Role Labeling for Video Understanding.

Motion has shown to be useful for video understanding, where motion is typically represented by optical flow. However, computing flow from video frames is very time-consuming....

The UCF101 dataset contains 13320 videos distributed in 101 action categories. This dataset is different from the above ones in that it contains mostly coarse sports activities...

The authors used the Kinetics-400, Something-Something-V2, and Epic-Kitchens-100 datasets for video understanding tasks.