56 datasets found

MoSeg is a dataset for object segmentation in videos.

The dataset used for local anomaly detection in videos using object-centric adversarial learning.

A large-scale video benchmark for human action recognition.

Weakly-supervised temporal action localization aims to identify and localize the action instances in the untrimmed videos with only video-level action labels.

The dataset is a collection of online videos from YouTube, with comments and metadata. It is used to evaluate the performance of the Online Video Clickbait Protector (OVCP) scheme.

The Subway Exit dataset contains video clips of people leaving a train station.

The Subway Entrance dataset contains video clips of people waiting to board a train.

CityCam dataset contains recordings from 212 traffic cameras in the United States, with a resolution of 352x240 and a frame rate of 1 frame/per second.

A large-scale database for partial copy detection in videos.

Tinyvideos dataset

The STV-IDL dataset is a collection of videos with referring expressions that describe spatio-temporal events.

The VisDrone2019 dataset contains 288 video clips made up of 261,908 frames and 10,209 images

A dataset of 30 videos of length 3 minutes to 20 minutes from five classes of daily activities: socializing, home repair, biking around urban areas, cooking, and home tours.

The ActivityNet1.2 dataset is a large-scale benchmark for action recognition and localization in videos.

Temporal sentence grounding in videos (TSGV) is a task to retrieve a video segment that semantically corresponds to a query in natural language.

InternVid: A large-scale video-text dataset for multimodal understanding and generation.

THUMOS Challenge: Action Recognition with a Large Number of Classes.

Generating human action proposals in untrimmed videos is an important yet challenging task with wide applications. Current methods often suffer from the noisy boundary locations...

The dataset contains videos of people performing normal activities and falls.

The dataset contains videos of people performing normal activities and falls.