A PyTorch re-implementation of the paper 'Exploring Simple Siamese Representation Learning'. Reproduced the 67.8% Top1 Acc on ImageNet.

Overview

Exploring simple siamese representation learning

This is a PyTorch re-implementation of the SimSiam paper on ImageNet dataset. The results match that reported in the paper. The implementation is based on the codes of MOCO.

Unsupervised pre-training

To run unsupervised pre-training on ImageNet,

sh train_simsiam.sh

This is to do the unsupervised pre-training for 100 epochs. Please modify the path to your ImageNet data folder.

Note 1: I try to follow the setting in the paper, which is bs=512 and lr=0.1 on 8-GPU, but somehow I can not fit it. So I used the max batch_size that I can fit (432) while kept the lr unchaged (0.1).

Note 2: In pre-training, I didn't fix the lr of prediction MLP. According to the paper (Table. 1), fixing the lr of prediction MLP can give slightly improvements (67.7% -> 68.1%). You can try it if interested.

Linear evaluation

To run linear evaluation,

sh train_lincls.sh

The linear evaluation is done using NVIDIA LARC optimizer by setting trus_coefficient=0.001 and clip=False. The batch size is 4096.

Note: I first followed the setting in the paper, which is Lr=0.32 (0.02*4096/256). But I can only got a result of 66.0%. Then I increased the learning rate to Lr=1.6 (0.1*4096.256) and achieved the result of 67.8%. The results and models are given below.

SimSiam pretrained batchsize lincls Lr Top-1 Acc
Reported 512 0.32 67.7%
Reproduced 432 (Model) 1.6 67.8% (Model)
Reproduced 432 0.32 66.0%

Acknowledgement

Thank Xinlei for his help on some implementation details.

Owner
Taojiannan Yang
PhD student at University of North Carolina at Charlotte.
Taojiannan Yang
Efficient 3D Backbone Network for Temporal Modeling

VoV3D is an efficient and effective 3D backbone network for temporal modeling implemented on top of PySlowFast. Diverse Temporal Aggregation and

102 Dec 06, 2022
This source code is implemented using keras library based on "Automatic ocular artifacts removal in EEG using deep learning"

CSP_Deep_EEG This source code is implemented using keras library based on "Automatic ocular artifacts removal in EEG using deep learning" {https://www

Seyed Mahdi Roostaiyan 2 Nov 08, 2022
Underwater image enhancement

LANet Our work proposes an adaptive learning attention network (LANet) to solve the problem of color casts and low illumination in underwater images.

LiuShiBen 7 Sep 14, 2022
Generative Adversarial Networks for High Energy Physics extended to a multi-layer calorimeter simulation

CaloGAN Simulating 3D High Energy Particle Showers in Multi-Layer Electromagnetic Calorimeters with Generative Adversarial Networks. This repository c

Deep Learning for HEP 101 Nov 13, 2022
Rethinking Portrait Matting with Privacy Preserving

Rethinking Portrait Matting with Privacy Preserving This is the official repository of the paper Rethinking Portrait Matting with Privacy Preserving.

184 Jan 03, 2023
Implementation of Cross Transformer for spatially-aware few-shot transfer, in Pytorch

Cross Transformers - Pytorch (wip) Implementation of Cross Transformer for spatially-aware few-shot transfer, in Pytorch Install $ pip install cross-t

Phil Wang 40 Dec 22, 2022
U-Net implementation in PyTorch for FLAIR abnormality segmentation in brain MRI

U-Net for brain segmentation U-Net implementation in PyTorch for FLAIR abnormality segmentation in brain MRI based on a deep learning segmentation alg

562 Jan 02, 2023
My Body is a Cage: the Role of Morphology in Graph-Based Incompatible Control

My Body is a Cage: the Role of Morphology in Graph-Based Incompatible Control

yobi byte 29 Oct 09, 2022
Training BERT with Compute/Time (Academic) Budget

Training BERT with Compute/Time (Academic) Budget This repository contains scripts for pre-training and finetuning BERT-like models with limited time

Intel Labs 263 Jan 07, 2023
World Models with TensorFlow 2

World Models This repo reproduces the original implementation of World Models. This implementation uses TensorFlow 2.2. Docker The easiest way to hand

Zac Wellmer 234 Nov 30, 2022
Autonomous Driving on Curvy Roads without Reliance on Frenet Frame: A Cartesian-based Trajectory Planning Method

C++/ROS Source Codes for "Autonomous Driving on Curvy Roads without Reliance on Frenet Frame: A Cartesian-based Trajectory Planning Method" published in IEEE Trans. Intelligent Transportation Systems

Bai Li 88 Dec 23, 2022
The source code of "SIDE: Center-based Stereo 3D Detector with Structure-aware Instance Depth Estimation", accepted to WACV 2022.

SIDE: Center-based Stereo 3D Detector with Structure-aware Instance Depth Estimation The source code of our work "SIDE: Center-based Stereo 3D Detecto

10 Dec 18, 2022
Deep Illuminator is a data augmentation tool designed for image relighting. It can be used to easily and efficiently generate a wide range of illumination variants of a single image.

Deep Illuminator Deep Illuminator is a data augmentation tool designed for image relighting. It can be used to easily and efficiently generate a wide

George Chogovadze 52 Nov 29, 2022
Answer a series of contextually-dependent questions like they may occur in natural human-to-human conversations.

SCAI-QReCC-21 [leaderboards] [registration] [forum] [contact] [SCAI] Answer a series of contextually-dependent questions like they may occur in natura

19 Sep 28, 2022
NHS AI Lab Skunkworks project: Long Stayer Risk Stratification

NHS AI Lab Skunkworks project: Long Stayer Risk Stratification A pilot project for the NHS AI Lab Skunkworks team, Long Stayer Risk Stratification use

NHSX 21 Nov 14, 2022
Pixel-level Crack Detection From Images Of Levee Systems : A Comparative Study

PIXEL-LEVEL CRACK DETECTION FROM IMAGES OF LEVEE SYSTEMS : A COMPARATIVE STUDY G

Manisha Panta 2 Jul 23, 2022
Implementation of DropLoss for Long-Tail Instance Segmentation in Pytorch

[AAAI 2021]DropLoss for Long-Tail Instance Segmentation [AAAI 2021] DropLoss for Long-Tail Instance Segmentation Ting-I Hsieh*, Esther Robb*, Hwann-Tz

Tim 37 Dec 02, 2022
Tensor-Based Quantum Machine Learning

TensorLy_Quantum TensorLy-Quantum is a Python library for Tensor-Based Quantum Machine Learning that builds on top of TensorLy and PyTorch. Website: h

TensorLy 85 Dec 03, 2022
A cross-lingual COVID-19 fake news dataset

CrossFake An English-Chinese COVID-19 fake&real news dataset from the ICDMW 2021 paper below: Cross-lingual COVID-19 Fake News Detection. Jiangshu Du,

Yingtong Dou 11 Dec 01, 2022
Using python and scikit-learn to make stock predictions

MachineLearningStocks in python: a starter project and guide EDIT as of Feb 2021: MachineLearningStocks is no longer actively maintained MachineLearni

Robert Martin 1.3k Dec 29, 2022