[ACM MM 2021] TSA-Net: Tube Self-Attention Network for Action Quality Assessment

Related tags

Deep LearningTSA-Net
Overview

Tube Self-Attention Network (TSA-Net)

This repository contains the PyTorch implementation for paper TSA-Net: Tube Self-Attention Network for Action Quality Assessment (ACM-MM'21 Oral)

[arXiv] [supp] [slides] [poster] [video]

If this repository is helpful to you, please star it. If you find our work useful in your research, please consider citing:

@inproceedings{TSA-Net,
  title={TSA-Net: Tube Self-Attention Network for Action Quality Assessment},
  author={Wang, Shunli and Yang, Dingkang and Zhai, Peng and Chen, Chixiao and Zhang, Lihua},
  booktitle={Proceedings of the 29th ACM International Conference on Multimedia},
  year={2021},
  pages={4902–4910},
  numpages={9}
}

User Guide

In this repository, we open source the code of TSA-Net on FR-FS dataset. The initialization process is as follows:

# 1.Clone this repository
git clone https://github.com/Shunli-Wang/TSA-Net.git ./TSA-Net
cd ./TSA-Net

# 2.Create conda env
conda create -n TSA-Net python
conda install pytorch torchvision torchaudio cudatoolkit=10.2 -c pytorch
pip install -r requirements.txt

# 3.Download pre-trained model and FRFS dataset. All download links are listed as follow.
# PATH/TO/rgb_i3d_pretrained.pt 
# PATH/TO/FRFS 

# 4.Create data dir
mkdir ./data && cd ./data
mv PATH/TO/rgb_i3d_pretrained.pt ./
ln -s PATH/TO/FRFS ./FRFS

After initialization, please check the data structure:

.
├── data
│   ├── FRFS -> PATH/TO/FRFS
│   └── rgb_i3d_pretrained.pt
├── dataset.py
├── train.py
├── test.py
...

Download links:

Training & Evaluation

We provide the training and testing code of TSA-Net and Plain-Net. The difference between the two is whether the TSA module exists. This option is controlled by --TSA item.

python train.py --gpu 0 --model_path TSA-USDL --TSA
python test.py --gpu 0 --pt_w Exp/TSA-USDL/best.pth --TSA

python train.py --gpu 0 --model_path USDL
python test.py --gpu 0 --pt_w Exp/USDL/best.pth

Acknowledgement

Our code is adapted from MUSDL. We are very grateful for their wonderful implementation. All tracking boxes in our project are generated by SiamMask. We also sincerely thank them for their contributions.

Contact

If you have any questions about our work, please contact [email protected].

Owner
ShunliWang
ShunliWang
Code for the CVPR2021 workshop paper "Noise Conditional Flow Model for Learning the Super-Resolution Space"

NCSR: Noise Conditional Flow Model for Learning the Super-Resolution Space Official NCSR training PyTorch Code for the CVPR2021 workshop paper "Noise

57 Oct 03, 2022
This repository contains the code for the paper 'PARM: Paragraph Aggregation Retrieval Model for Dense Document-to-Document Retrieval' published at ECIR'22.

Paragraph Aggregation Retrieval Model (PARM) for Dense Document-to-Document Retrieval This repository contains the code for the paper PARM: A Paragrap

Sophia Althammer 33 Aug 26, 2022
A system for quickly generating training data with weak supervision

Programmatically Build and Manage Training Data Announcement The Snorkel team is now focusing their efforts on Snorkel Flow, an end-to-end AI applicat

Snorkel Team 5.4k Jan 02, 2023
Using Tensorflow Object Detection API to detect Waymo open dataset

Waymo-2D-Object-Detection Using Tensorflow Object Detection API to detect Waymo open dataset Result CenterNet Training Loss SSD ResNet Training Loss C

76 Dec 12, 2022
Code for training and evaluation of the model from "Language Generation with Recurrent Generative Adversarial Networks without Pre-training"

Language Generation with Recurrent Generative Adversarial Networks without Pre-training Code for training and evaluation of the model from "Language G

Amir Bar 253 Sep 14, 2022
TinyML Cookbook, published by Packt

TinyML Cookbook This is the code repository for TinyML Cookbook, published by Packt. Author: Gian Marco Iodice Publisher: Packt About the book This bo

Packt 93 Dec 29, 2022
Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models.

Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models

AdvBox 1.3k Dec 25, 2022
PyTorch implementation for the paper Visual Representation Learning with Self-Supervised Attention for Low-Label High-Data Regime

Visual Representation Learning with Self-Supervised Attention for Low-Label High-Data Regime Created by Prarthana Bhattacharyya. Disclaimer: This is n

Prarthana Bhattacharyya 5 Nov 08, 2022
Python Jupyter kernel using Poetry for reproducible notebooks

Poetry Kernel Use per-directory Poetry environments to run Jupyter kernels. No need to install a Jupyter kernel per Python virtual environment! The id

Pathbird 204 Jan 04, 2023
Bayesian inference for Permuton-induced Chinese Restaurant Process (NeurIPS2021).

Permuton-induced Chinese Restaurant Process Note: Currently only the Matlab version is available, but a Python version will be available soon! This is

NTT Communication Science Laboratories 3 Dec 17, 2022
Code related to the manuscript "Averting A Crisis In Simulation-Based Inference"

Abstract We present extensive empirical evidence showing that current Bayesian simulation-based inference algorithms are inadequate for the falsificat

Montefiore Artificial Intelligence Research 3 Nov 14, 2022
CrossNorm and SelfNorm for Generalization under Distribution Shifts (ICCV 2021)

CrossNorm (CN) and SelfNorm (SN) (Accepted at ICCV 2021) This is the official PyTorch implementation of our CNSN paper, in which we propose CrossNorm

100 Dec 28, 2022
Code for "Diffusion is All You Need for Learning on Surfaces"

Source code for "Diffusion is All You Need for Learning on Surfaces", by Nicholas Sharp Souhaib Attaiki Keenan Crane Maks Ovsjanikov NOTE: the linked

Nick Sharp 247 Dec 28, 2022
Evaluating Cross-lingual Sentence Representations

XNLI: The Cross-Lingual NLI Corpus XNLI is an evaluation corpus for language transfer and cross-lingual sentence classification in 15 languages. New:

Meta Research 395 Dec 19, 2022
AFLNet: A Greybox Fuzzer for Network Protocols

AFLNet: A Greybox Fuzzer for Network Protocols AFLNet is a greybox fuzzer for protocol implementations. Unlike existing protocol fuzzers, it takes a m

626 Jan 06, 2023
PyTorch implementation of the R2Plus1D convolution based ResNet architecture described in the paper "A Closer Look at Spatiotemporal Convolutions for Action Recognition"

R2Plus1D-PyTorch PyTorch implementation of the R2Plus1D convolution based ResNet architecture described in the paper "A Closer Look at Spatiotemporal

Irhum Shafkat 342 Dec 16, 2022
Performant, differentiable reinforcement learning

deluca Performant, differentiable reinforcement learning Notes This is pre-alpha software and is undergoing a number of core changes. Updates to follo

Google 114 Dec 27, 2022
A library for uncertainty quantification based on PyTorch

Torchuq [logo here] TorchUQ is an extensive library for uncertainty quantification (UQ) based on pytorch. TorchUQ currently supports 10 representation

TorchUQ 96 Dec 12, 2022
😮The official implementation of "CoNeRF: Controllable Neural Radiance Fields" 😮

CoNeRF: Controllable Neural Radiance Fields This is the official implementation for "CoNeRF: Controllable Neural Radiance Fields" Project Page Paper V

Kacper Kania 61 Dec 24, 2022
Self-Supervised Image Denoising via Iterative Data Refinement

Self-Supervised Image Denoising via Iterative Data Refinement Yi Zhang1, Dasong Li1, Ka Lung Law2, Xiaogang Wang1, Hongwei Qin2, Hongsheng Li1 1CUHK-S

Zhang Yi 72 Jan 01, 2023