https://github.com/wanglimin/UntrimmedNet

Weakly Supervised Action Recognition and Detection
https://github.com/wanglimin/UntrimmedNet

action-detection action-recognition weakly-supervised-learning

Last synced: 18 days ago
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Weakly Supervised Action Recognition and Detection

• Host: GitHub
• URL: https://github.com/wanglimin/UntrimmedNet
• Owner: wanglimin
• Created: 2017-03-08T09:43:26.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2018-10-16T06:37:39.000Z (over 5 years ago)
• Last Synced: 2024-02-26T22:40:14.795Z (4 months ago)
• Topics: action-detection, action-recognition, weakly-supervised-learning
• Language: Matlab
• Homepage:
• Size: 1.23 MB
• Stars: 163
• Watchers: 18
• Forks: 47
• Open Issues: 6
• Metadata Files:
  • Readme: README.md

Lists

• Awesome-Caffe - UntrimmedNets

README

        
# UntrimmedNet for Action Recognition and Detection

We provide the code and models for our CVPR paper ([Arxiv Preprint](https://arxiv.org/abs/1703.03329)):

      UntrimmedNets for Weakly Supervised Action Recognition and Detection

      Limin Wang, Yuanjun Xiong, Dahua Lin, and Luc Van Gool

      in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017

### Updates

- October 16th, 2018

  * Release the learned models trained only on the train set of ActivityNet1.2 datasets. Note that our previously released ActivityNet models are trained on the train+val set. 

- September 19th, 2017

  * Release the learned models on the THUMOS14 and ActivityNet1.2 datasets.

- August 20th, 2017

  * Release the model protos.

  

### Guide

The training of UntrimmedNet is composed of three steps:

- **Step 1**: extract action proposals (or shot boundaries) for each untrimmed video. We provide a sample of detected shot boudary on the ActivityNet (v1.2) under the folders of `data/anet1.2/anet_1.2_train_window_shot/` and `data/anet1.2/anet1.2/anet_1.2_val_window_shot/`.

- **Step 2**: construct file lists for training and validation. There are two filelists: one containing file path, number of frames, and label; the other one containing the shot file path and number of frames (Examples are in the folder `data/anet1.2/`).

- **Step 3**: train UntrimmedNets using our modified caffe: https://github.com/yjxiong/caffe/tree/untrimmednet

The testing of UntrimmedNet for action recognition is based on temporal sliding window and top-k pooling

The testing of UntrimmedNet for action detection is based on  a simple baseline (see code in `matlab/`）

### Downloads

You could download our trained models on the THUMOS14 and ActivityNet datasets by using the scripts of `scripts/get_reference_model_thumos.sh` and `scripts/get_reference_model_anet.sh`.