/SSAD

Pytorch implementation of SSAD for temporal action detection

Primary LanguagePython

Single Shot Temporal Action Detection

A pytorch-version implementation codes of paper: "Single Shot Temporal Action Detection", which is accepted in ACM MM 2017. paper

This repository is an improved version for the anchor-based part of A2Net.

If you find the repository helpful to you, here is a version that combines anchor-based module and anchor-free module: MSA-Net.

Result

The detection results on THUMOS14 dataset:

mAP@ 0.3 0.4 0.5 0.6 0.7
61.83 58.03 51.12 35.93 20.72

Prerequisites

This repository is implemented with Pytorch 1.1.0 + Python3.

Download Datasets

The Two stream I3D feature could be downloaded from A2Net.

Training and Testing of SSAD

  1. To train the SSAD:
cd tools
python main.py

The parameters could be modified in

experiments\thumos\SSAD_train.yaml
  1. To Test the SSAD:
cd tools
python eval.py --checkpoint $cpt_path
  1. Evaluating the detection performance:

Open Matlab in lib\Evaluation\THUMOS14_evalkit_20150930 path, and put the testing result file in the path, and execute the file:

multi_iou_eval