KO
|
EN
gitlite — search
Search
#javascript
#python
#hacktoberfest
#react
#ai
#typescript
#llm
#go
#golang
#android
#machine-learning
#rust
#deep-learning
#linux
weakly-action-localization
★ 30
Open GitHub ↗
No description available.
Download README (.md)
Explore Similar Repositories
CBP
:
Official Tensorflow Implementation of the AAAI-2020 paper "Temporally Grounding Language Queries in Videos by Contextual Boundary-aware Prediction"
3c-net
:
Weakly-supervised Action Localization
StandardActions
:
Standard actions for SwiftUI, localized in 8 languages.
LookForTheChange
:
Code for Look for the Change paper published at CVPR 2022
VLM-Video-Action-Localization
:
No description available.
// repository documentation
Was this content helpful?
★ 0
(0 ratings)
Select Rating:
★
★
★
★
★
Submit Feedback
Recent Feedback
×
Download README
Do you want to download the
README.md
file for
weakly-action-localization
?
Download (.md)
# Weakly Supervised Action Localization by Sparse Temporal Pooling Network ## Overview This repository contains reproduced code reported in the paper "[Weakly Supervised Action Localization by Sparse Temporal Pooling Network](https://arxiv.org/abs/1712.05080)" by Phuc Nguyen and Ting Liu. The paper was posted on arXiv in Dec 2017, published as a CVPR 2018 conference paper. Disclaimer: This is the reproduced code, not an original code of the paper. ## Running the code see the multi_run.sh firstly you need to use [Dense_Flow](https://github.com/yjxiong/dense_flow) to extract rgb and optical flow secondly you need to extract I3D feature using [thumos14-i3d](https://github.com/demianzhang/thumos14-i3d) finally you can train, test and combine the rgb and flow result ### result Model | 0.1 | 0.2 | 0.3 | 0.4 | 0.5 -------------- | :---: | :---: | :---: | :---: | ---- RGB-I3D | 0.351 | 0.279 | 0.213 | 0.150 | 0.102 Flow-I3D | 0.408 | 0.340 | 0.269 | 0.205 | 0.144 Two-Stream I3D | - | - | - | - | - ### please pay attention to the order according to the paper 1. sample 10fps use opencv cv2.VideoCapture to read the video and keep one frame every three frames[original video in 30fps] 2. keep ratio 340x180 and resize the small edge to 256 after resize frames, then use cv2.VideoWriter to save sampled frames into video 3. extract flow use dense_flow to extract rgb and flows, please pay attention to the shell default parameter 340x256, you should change it to the video's shape in order to keep the ratio 4. center crop 224x224, each 16 frames are sent to i3d The result may be a little higher than the result, because I did not obey this order before.
