Official PyTorch Implementation of Learning Self-Similarity in Space and Time as Generalized Motion for Video Action Recognition, ICCV 2021

Related tags

Deep LearningSELFY
Overview

Learning Self-Similarity in Space and Time as Generalized Motion for Video Action Recognition


SELFY_block


This is the official implementation of the paper "Learning Self-Similarity in Space and Time as Generalized Motion for Video Action Recognition" by H.Kwon, M.Kim, S.Kwak, and M.Cho. For more information, checkout the project website and the paper on arXiv.

Environment:

Anaconda environment setting

git clone https://github.com/arunos728/SELFY.git
cd selfy
conda env create -f environment.yml
conda activate selfy

Installing Correlation sampler

cd Pytorch-Correlation-extension
python setup.py install

# check whether SpatialCorrelationSampler is installed correctly.
python check.py forward
python check.py backward
python checkCorrelationSampler.py

Please check this repo for the detailed instructions.

Dataset preparation

Please refer to TSM repo for the detailed data preparation instructions.

File lists (.txt files in ./data) specify configurations of each video clips (path, #frames, class). We upload our Something-Something-V1 & V2 video file lists in ./data. The path of the file lists should be added into the scripts for training (or testing).

Training & Testing

  • For training SELFYNet on Something-Something, use the following command:
    ./scripts/train_SELFY_Something.sh
  • For testing your trained model on Something-Something, use the following command:
    ./scripts/test_SELFY_Something.sh

Citation

If you use this code or ideas from the paper for your research, please cite our paper:

@inproceedings{kwon2021learning,
  title={Learning self-similarity in space and time as generalized motion for video action recognition},
  author={Kwon, Heeseung and Kim, Manjin and Kwak, Suha and Cho, Minsu},
  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
  pages={13065--13075},
  year={2021}
}

Contact

Heeseung Kwon([email protected]), Manjin Kim([email protected])

Questions can also be left as issues in the repository. We will be happy to answer them.

AugLiChem - The augmentation library for chemical systems.

AugLiChem Welcome to AugLiChem! The augmentation library for chemical systems. This package supports augmentation for both crystaline and molecular sy

BaratiLab 17 Jan 08, 2023
🐦 Quickly annotate data from the comfort of your Jupyter notebook

🐦 pigeon - Quickly annotate data on Jupyter Pigeon is a simple widget that lets you quickly annotate a dataset of unlabeled examples from the comfort

Anastasis Germanidis 647 Jan 05, 2023
This repository contains an implementation of ConvMixer for the ICLR 2022 submission "Patches Are All You Need?".

Patches Are All You Need? 🤷 This repository contains an implementation of ConvMixer for the ICLR 2022 submission "Patches Are All You Need?". Code ov

ICLR 2022 Author 934 Dec 30, 2022
Pipeline code for Sequential-GAM(Genome Architecture Mapping).

Sequential-GAM Pipeline code for Sequential-GAM(Genome Architecture Mapping). mapping whole_preprocess.sh include the whole processing of mapping. usa

3 Nov 03, 2022
Pytorch implementation of the paper SPICE: Semantic Pseudo-labeling for Image Clustering

SPICE: Semantic Pseudo-labeling for Image Clustering By Chuang Niu and Ge Wang This is a Pytorch implementation of the paper. (In updating) SOTA on 5

Chuang Niu 154 Dec 15, 2022
Tensorflow implementation of MIRNet for Low-light image enhancement

MIRNet Tensorflow implementation of the MIRNet architecture as proposed by Learning Enriched Features for Real Image Restoration and Enhancement. Lanu

Soumik Rakshit 91 Jan 06, 2023
A Large-Scale Dataset for Spinal Vertebrae Segmentation in Computed Tomography

A Large-Scale Dataset for Spinal Vertebrae Segmentation in Computed Tomography

ICT.MIRACLE lab 75 Dec 26, 2022
UNION: An Unreferenced Metric for Evaluating Open-ended Story Generation

UNION Automatic Evaluation Metric described in the paper UNION: An UNreferenced MetrIc for Evaluating Open-eNded Story Generation (EMNLP 2020). Please

50 Dec 30, 2022
Unofficial implementation of the ImageNet, CIFAR 10 and SVHN Augmentation Policies learned by AutoAugment using pillow

AutoAugment - Learning Augmentation Policies from Data Unofficial implementation of the ImageNet, CIFAR10 and SVHN Augmentation Policies learned by Au

Philip Popien 1.3k Jan 02, 2023
[UNMAINTAINED] Automated machine learning for analytics & production

auto_ml Automated machine learning for production and analytics Installation pip install auto_ml Getting started from auto_ml import Predictor from au

Preston Parry 1.6k Jan 02, 2023
Using deep actor-critic model to learn best strategies in pair trading

Deep-Reinforcement-Learning-in-Stock-Trading Using deep actor-critic model to learn best strategies in pair trading Abstract Partially observed Markov

281 Dec 09, 2022
Capsule endoscopy detection DACON challenge

capsule_endoscopy_detection (DACON Challenge) Overview Yolov5, Yolor, mmdetection기반의 모델을 사용 (총 11개 모델 앙상블) 모든 모델은 학습 시 Pretrained Weight을 yolov5, yolo

MAILAB 11 Nov 25, 2022
DetCo: Unsupervised Contrastive Learning for Object Detection

DetCo: Unsupervised Contrastive Learning for Object Detection arxiv link News Sparse RCNN+DetCo improves from 45.0 AP to 46.5 AP(+1.5) with 3x+ms trai

Enze Xie 234 Dec 18, 2022
Hyperparameter Optimization for TensorFlow, Keras and PyTorch

Hyperparameter Optimization for Keras Talos • Key Features • Examples • Install • Support • Docs • Issues • License • Download Talos radically changes

Autonomio 1.6k Dec 15, 2022
In this project, we develop a face recognize platform based on MTCNN object-detection netcwork and FaceNet self-supervised network.

模式识别大作业——人脸检测与识别平台 本项目是一个简易的人脸检测识别平台,提供了人脸信息录入和人脸识别的功能。前端采用 html+css+js,后端采用 pytorch,

Xuhua Huang 5 Aug 02, 2022
Implementation of H-UCRL Algorithm

Implementation of H-UCRL Algorithm This repository is an implementation of the H-UCRL algorithm introduced in Curi, S., Berkenkamp, F., & Krause, A. (

Sebastian Curi 25 May 20, 2022
This code is for eCaReNet: explainable Cancer Relapse Prediction Network.

eCaReNet This code is for eCaReNet: explainable Cancer Relapse Prediction Network. (Towards Explainable End-to-End Prostate Cancer Relapse Prediction

Institute of Medical Systems Biology 2 Jul 28, 2022
Rule Extraction Methods for Interactive eXplainability

REMIX: Rule Extraction Methods for Interactive eXplainability This repository contains a variety of tools and methods for extracting interpretable rul

Mateo Espinosa Zarlenga 21 Jan 03, 2023
Koç University deep learning framework.

Knet Knet (pronounced "kay-net") is the Koç University deep learning framework implemented in Julia by Deniz Yuret and collaborators. It supports GPU

1.4k Dec 31, 2022
Restricted Boltzmann Machines in Python.

How to Use First, initialize an RBM with the desired number of visible and hidden units. rbm = RBM(num_visible = 6, num_hidden = 2) Next, train the m

Edwin Chen 928 Dec 30, 2022