PyTorch implementation code for the paper MixCo: Mix-up Contrastive Learning for Visual Representation

Overview

How to Reproduce our Results

This repository contains PyTorch implementation code for the paper MixCo: Mix-up Contrastive Learning for Visual Representation (https://arxiv.org/abs/2010.06300) that is accepted in NeurIPS 2020 Workshop on Self-Supervised Learning.

This is an instruction to reproduce our results, based on the source code we have provided.

Prerequisites

  1. You should download the Tiny-ImageNet dataset. To download the images, go to https://tiny-imagenet.herokuapp.com/ and click 'Download Tiny ImageNet' button. Equivalently, try
wget http://cs231n.stanford.edu/tiny-imagenet-200.zip 
  1. Unzip the file and place the folder into [your_data_path].
  2. Also, download the ImageNet train dataset.
  3. For linear classification, you may also need CIFAR10 and CIFAR100 dataset. If you do not have them, give the argument --download when running lincls.py. Then, it will download the dataset before training.

Structure

This repository contains python files that can train the model with mixup-based representaion learning.

pretrain.py pretrains the model in unsupervised manner, and saves the encoder part (without classification layers).

lincls.py loads and freezes the pretrained model, and then train the classifier part on the target dataset.

Experiments

  1. In ./moco/experiments/ and ./simclr/scripts/, there are .sh files which include the commands that can reproduce our experimental results. Open and set the configs.
data_path="[your_data_path]"
exp_name="[experiment_name]"
  1. Run the file. For example, if you want to pretrain the ResNet18 model with Tiny-ImageNet, and then see the linear classification results, run exp_mix_res18_tinyimg.sh.
bash experiments/exp_mix_res18_tinyimg.sh
  1. You can find the pretraining and linear evaluation results in results/results.json file.
Owner
opcrisis
opcrisis
[CVPR2021 Oral] UP-DETR: Unsupervised Pre-training for Object Detection with Transformers

UP-DETR: Unsupervised Pre-training for Object Detection with Transformers This is the official PyTorch implementation and models for UP-DETR paper: @a

dddzg 430 Dec 23, 2022
Mmdet benchmark with python

mmdet_benchmark 本项目是为了研究 mmdet 推断性能瓶颈,并且对其进行优化。 配置与环境 机器配置 CPU:Intel(R) Core(TM) i9-10900K CPU @ 3.70GHz GPU:NVIDIA GeForce RTX 3080 10GB 内存:64G 硬盘:1T

杨培文 (Yang Peiwen) 24 May 21, 2022
UltraGCN: An Ultra Simplification of Graph Convolutional Networks for Recommendation

UltraGCN This is our Pytorch implementation for our CIKM 2021 paper: Kelong Mao, Jieming Zhu, Xi Xiao, Biao Lu, Zhaowei Wang, Xiuqiang He. UltraGCN: A

XUEPAI 93 Jan 03, 2023
A Tensorflow implementation of BicycleGAN.

BicycleGAN implementation in Tensorflow As part of the implementation series of Joseph Lim's group at USC, our motivation is to accelerate (or sometim

Cognitive Learning for Vision and Robotics (CLVR) lab @ USC 97 Dec 02, 2022
Official Pytorch implementation of C3-GAN

Official pytorch implemenation of C3-GAN Contrastive Fine-grained Class Clustering via Generative Adversarial Networks [Paper] Authors: Yunji Kim, Jun

NAVER AI 114 Dec 02, 2022
Orthogonal Over-Parameterized Training

The inductive bias of a neural network is largely determined by the architecture and the training algorithm. To achieve good generalization, how to effectively train a neural network is of great impo

Weiyang Liu 11 Apr 18, 2022
Metrics to evaluate quality and efficacy of synthetic datasets.

An Open Source Project from the Data to AI Lab, at MIT Metrics for Synthetic Data Generation Projects Website: https://sdv.dev Documentation: https://

The Synthetic Data Vault Project 129 Jan 03, 2023
Planar Prior Assisted PatchMatch Multi-View Stereo

ACMP [News] The code for ACMH is released!!! [News] The code for ACMM is released!!! About This repository contains the code for the paper Planar Prio

Qingshan Xu 127 Dec 31, 2022
Skyformer: Remodel Self-Attention with Gaussian Kernel and Nystr\"om Method (NeurIPS 2021)

Skyformer This repository is the official implementation of Skyformer: Remodel Self-Attention with Gaussian Kernel and Nystr"om Method (NeurIPS 2021).

Qi Zeng 46 Sep 20, 2022
Implementation of the ivis algorithm as described in the paper Structure-preserving visualisation of high dimensional single-cell datasets.

Implementation of the ivis algorithm as described in the paper Structure-preserving visualisation of high dimensional single-cell datasets.

beringresearch 285 Jan 04, 2023
A python package to perform same transformation to coco-annotation as performed on the image.

coco-transform-util A python package to perform same transformation to coco-annotation as performed on the image. Installation Way 1 $ git clone https

1 Jan 14, 2022
Code samples for my book "Neural Networks and Deep Learning"

Code samples for "Neural Networks and Deep Learning" This repository contains code samples for my book on "Neural Networks and Deep Learning". The cod

Michael Nielsen 13.9k Dec 26, 2022
Transformer in Vision

Transformer-in-Vision Recent Transformer-based CV and related works. Welcome to comment/contribute! Keep updated. Resource SCENIC: A JAX Library for C

Yong-Lu Li 1.1k Dec 30, 2022
Transformer in Computer Vision

Transformer-in-Vision A paper list of some recent Transformer-based CV works. If you find some ignored papers, please open issues or pull requests. **

506 Dec 26, 2022
This repository includes code of my study about Asynchronous in Frequency domain of GAN images.

Exploring the Asynchronous of the Frequency Spectra of GAN-generated Facial Images Binh M. Le & Simon S. Woo, "Exploring the Asynchronous of the Frequ

4 Aug 06, 2022
DANet for Tabular data classification/ regression.

Deep Abstract Networks A PyTorch code implemented for the submission DANets: Deep Abstract Networks for Tabular Data Classification and Regression. Do

Ronnie Rocket 55 Sep 14, 2022
Music library streaming app written in Flask & VueJS

djtaytay This is a little toy app made to explore Vue, brush up on my Python, and make a remote music collection accessable through a web interface. I

Ryan Tasson 6 May 27, 2022
Unity Propagation in Bayesian Networks Handling Inconsistency via Unity Smoothing

This repository contains the scripts needed to generate the results from the paper Unity Propagation in Bayesian Networks Handling Inconsistency via U

0 Jan 19, 2022
Scalable and Elastic Deep Reinforcement Learning Using PyTorch. Please star. 🔥

ElegantRL “小雅”: Scalable and Elastic Deep Reinforcement Learning ElegantRL is developed for researchers and practitioners with the following advantage

AI4Finance Foundation 2.5k Jan 05, 2023
It is the assignment for COMP 576 in Rice University

COMP-576 It is the assignment for COMP 576 in Rice University There are two programming assignments and one Final Project. Assignment 1: It is a MLP a

Maojie Tang 1 Nov 25, 2021