Temporal Action Localization

308 papers with code • 10 benchmarks • 39 datasets

Temporal Action Localization aims to detect activities in the video stream and output beginning and end timestamps. It is closely related to Temporal Action Proposal Generation.

Libraries

Use these libraries to find Temporal Action Localization models and implementations

Most implemented papers

Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition

yysijie/st-gcn 23 Jan 2018

Dynamics of human body skeletons convey significant information for human action recognition.

Grad-CAM++: Improved Visual Explanations for Deep Convolutional Networks

adityac94/Grad_CAM_plus_plus 30 Oct 2017

Over the last decade, Convolutional Neural Network (CNN) models have been highly successful in solving complex vision problems.

Temporal Segment Networks: Towards Good Practices for Deep Action Recognition

yjxiong/temporal-segment-networks 2 Aug 2016

The other contribution is our study on a series of good practices in learning ConvNets on video data with the help of temporal segment network.

BSN: Boundary Sensitive Network for Temporal Action Proposal Generation

wzmsltw/BSN-boundary-sensitive-network.pytorch ECCV 2018

Temporal action proposal generation is an important yet challenging problem, since temporal proposals with rich action content are indispensable for analysing real-world videos with long duration and high proportion irrelevant content.

A Closer Look at Spatiotemporal Convolutions for Action Recognition

facebookresearch/R2Plus1D CVPR 2018

In this paper we discuss several forms of spatiotemporal convolutions for video analysis and study their effects on action recognition.

BMN: Boundary-Matching Network for Temporal Action Proposal Generation

PaddlePaddle/models ICCV 2019

To address these difficulties, we introduce the Boundary-Matching (BM) mechanism to evaluate confidence scores of densely distributed proposals, which denote a proposal as a matching pair of starting and ending boundaries and combine all densely distributed BM pairs into the BM confidence map.

Unsupervised Learning of Video Representations using LSTMs

emansim/unsupervised-videos 16 Feb 2015

We further evaluate the representations by finetuning them for a supervised learning problem - human action recognition on the UCF-101 and HMDB-51 datasets.

Temporal Segment Networks for Action Recognition in Videos

yjxiong/temporal-segment-networks 8 May 2017

Furthermore, based on the temporal segment networks, we won the video classification track at the ActivityNet challenge 2016 among 24 teams, which demonstrates the effectiveness of TSN and the proposed good practices.

Multivariate LSTM-FCNs for Time Series Classification

houshd/MLSTM-FCN 14 Jan 2018

Over the past decade, multivariate time series classification has received great attention.

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

wushidonguc/two-stream-action-recognition-keras 3 Dec 2012

To the best of our knowledge, UCF101 is 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.