Weakly Supervised Temporal Action Localization

23 papers with code • 1 benchmarks • 2 datasets

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Libraries

Use these libraries to find Weakly Supervised Temporal Action Localization models and implementations

Most implemented papers

Weakly Supervised Action Localization by Sparse Temporal Pooling Network

demianzhang/weakly-action-localization CVPR 2018

We propose a weakly supervised temporal action localization algorithm on untrimmed videos using convolutional neural networks.

Background Suppression Network for Weakly-supervised Temporal Action Localization

Pilhyeon/BaSNet-pytorch 22 Nov 2019

This formulation does not fully model the problem in that background frames are forced to be misclassified as action classes to predict video-level labels accurately.

Weakly-supervised Temporal Action Localization by Uncertainty Modeling

Pilhyeon/WTAL-Uncertainty-Modeling 12 Jun 2020

Experimental results show that our uncertainty modeling is effective at alleviating the interference of background frames and brings a large performance gain without bells and whistles.

ACM-Net: Action Context Modeling Network for Weakly-Supervised Temporal Action Localization

ispc-lab/ACM-Net 7 Apr 2021

Traditional methods mainly focus on foreground and background frames separation with only a single attention branch and class activation sequence.

AutoLoc: Weakly-supervised Temporal Action Localization

zhengshou/AutoLoc 22 Jul 2018

In this paper, we first develop a novel weakly-supervised TAL framework called AutoLoc to directly predict the temporal boundary of each action instance.

RefineLoc: Iterative Refinement for Weakly-Supervised Action Localization

HumamAlwassel/RefineLoc 30 Mar 2019

RefineLoc shows competitive results with the state-of-the-art in weakly-supervised temporal localization.

Completeness Modeling and Context Separation for Weakly Supervised Temporal Action Localization

Finspire13/CMCS-Temporal-Action-Localization CVPR 2019

In this work, we first identify two underexplored problems posed by the weak supervision for temporal action localization, namely action completeness modeling and action-context separation.

3C-Net: Category Count and Center Loss for Weakly-Supervised Action Localization

naraysa/3c-net ICCV 2019

Our joint formulation has three terms: a classification term to ensure the separability of learned action features, an adapted multi-label center loss term to enhance the action feature discriminability and a counting loss term to delineate adjacent action sequences, leading to improved localization.

Weakly Supervised Temporal Action Localization Using Deep Metric Learning

asrafulashiq/wsad 21 Jan 2020

We propose a classification module to generate action labels for each segment in the video, and a deep metric learning module to learn the similarity between different action instances.

Weakly-Supervised Action Localization by Generative Attention Modeling

bfshi/DGAM-Weakly-Supervised-Action-Localization CVPR 2020

By maximizing the conditional probability with respect to the attention, the action and non-action frames are well separated.