UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild

12/03/2012
by   Khurram Soomro, et al.
0

We introduce UCF101 which is currently the largest dataset of human actions. It consists of 101 action classes, over 13k clips and 27 hours of video data. The database consists of realistic user uploaded videos containing camera motion and cluttered background. Additionally, we provide baseline action recognition results on this new dataset using standard bag of words approach with overall performance of 44.5 currently the most challenging dataset of actions due to its large number of classes, large number of clips and also unconstrained nature of such clips.

READ FULL TEXT

page 2

page 3

page 4

page 5

page 7

research
06/06/2020

ARID: A New Dataset for Recognizing Action in the Dark

The task of action recognition in dark videos is useful in various scena...
research
06/07/2016

Hand Action Detection from Ego-centric Depth Sequences with Error-correcting Hough Transform

Detecting hand actions from ego-centric depth sequences is a practically...
research
06/12/2020

ESAD: Endoscopic Surgeon Action Detection Dataset

In this work, we take aim towards increasing the effectiveness of surgic...
research
06/27/2021

Building a Video-and-Language Dataset with Human Actions for Multimodal Logical Inference

This paper introduces a new video-and-language dataset with human action...
research
07/21/2015

Every Moment Counts: Dense Detailed Labeling of Actions in Complex Videos

Every moment counts in action recognition. A comprehensive understanding...
research
09/09/2016

Image and Video Mining through Online Learning

Within the field of image and video recognition, the traditional approac...
research
04/07/2021

The SARAS Endoscopic Surgeon Action Detection (ESAD) dataset: Challenges and methods

For an autonomous robotic system, monitoring surgeon actions and assisti...

Please sign up or login with your details

Forgot password? Click here to reset