Skip to content
/ MCA Public

A PyTorch implementation of MCA based on PRICAI 2022 paper "Weakly-supervised Temporal Action Localization with Multi-head Cross-modal Attention"

Notifications You must be signed in to change notification settings

leftthomas/MCA

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

54 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

MCA

A PyTorch implementation of MCA based on PRICAI 2022 paper Weakly-supervised Temporal Action Localization with Multi-head Cross-modal Attention.

Network Architecture

Usage

Git clone the corresponding repos and replace the files provided by us, then run the code according to readme of corresponding repos.

For example, to train HAM-Net on THUMOS14 dataset:

git clone https://github.com/asrafulashiq/hamnet.git
mv AGCT/hamnet/* hamnet/
python main.py

To evaluate HAM-Net on THUMOS14 dataset:

python main.py --test --ckpt [checkpoint_path]

Benchmarks

The models are trained on one NVIDIA GeForce TITAN X GPU (12G). All the hyper-parameters are the default values.

THUMOS14

Method THUMOS14 Download
[email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] mAP@AVG
HAM-Net 66.8 60.9 52.2 42.9 33.4 22.7 12.2 41.6 OneDrive
CoLA 67.5 60.6 51.9 43.2 34.2 24.2 13.9 42.2 OneDrive
CO2-Net 70.8 64.7 55.7 46.8 39.8 26.5 13.8 45.4 OneDrive

mAP@AVG is the average mAP under the thresholds 0.1:0.1:0.7.

ActivityNet

Method ActivityNet 1.2 Download
[email protected] [email protected] [email protected] mAP@AVG
HAM-Net 41.3 25.2 5.5 25.4 OneDrive
CoLA 41.0 27.5 4.2 26.4 OneDrive
CO2-Net 44.4 27.0 5.4 27.1 OneDrive

mAP@AVG is the average mAP under the thresholds 0.5:0.05:0.95.

Results

vis

About

A PyTorch implementation of MCA based on PRICAI 2022 paper "Weakly-supervised Temporal Action Localization with Multi-head Cross-modal Attention"

Topics

Resources

Stars

Watchers

Forks

Languages