Code for the paper "M2m: Imbalanced Classification via Major-to-minor Translation" (CVPR 2020)

Related tags

Deep LearningM2m
Overview

M2m: Imbalanced Classification via Major-to-minor Translation

This repository contains code for the paper "M2m: Imbalanced Classification via Major-to-minor Translation" by Jaehyung Kim*, Jongheon Jeong* and Jinwoo Shin.

Dependencies

  • python3
  • pytorch >= 1.1.0
  • torchvision
  • tqdm

Scripts

Please check out run.sh for all the scripts to reproduce the CIFAR-10-LT results reported.

Training procedure of M2m

  1. Train a baseline network g for generating minority samples
python train.py --no_over --ratio 100 --decay 2e-4 --model resnet32 --dataset cifar10 \
--lr 0.1 --batch-size 128 --name 'ERM' --warm 200 --epoch 200
  1. Train another network f using M2m with the pre-trained g
python train.py -gen -r --ratio 100 --decay 2e-4 --model resnet32 --dataset cifar10 \
--lr 0.1 --batch-size 128 --name 'M2m' --beta 0.999 --lam 0.5 --gamma 0.9 \
--step_size 0.1 --attack_iter 10 --warm 160 --epoch 200 --net_g ./checkpoint/pre_trained_g.t7

We also provide a pre-trained ResNet-32 model of g at checkpoint/erm_r100_c10_trial1.t7, so one can directly use M2m without pre-training as follows:

python train.py -gen -r --ratio 100 --decay 2e-4 --model resnet32 --dataset cifar10 \
--lr 0.1 --batch-size 128 --name 'M2m' --beta 0.999 --lam 0.5 --gamma 0.9 \
--step_size 0.1 --attack_iter 10 --warm 160 --epoch 200 --net_g ./checkpoint/erm_r100_c10_trial1.t7
Owner
GitHub Repository http://arxiv.org/abs/2004.00431
Deep metric learning methods implemented in Chainer

Deep Metric Learning Implementation of several methods for deep metric learning in Chainer v4.2.0. Proxy-NCA: No Fuss Distance Metric Learning using P

ronekko 156 Nov 28, 2022
Towards Multi-Camera 3D Human Pose Estimation in Wild Environment

PanopticStudio Toolbox This repository has a toolbox to download, process, and visualize the Panoptic Studio (Panoptic) data. Note: Sep-21-2020: Curre

335 Jan 09, 2023
Learning Generative Models of Textured 3D Meshes from Real-World Images, ICCV 2021

Learning Generative Models of Textured 3D Meshes from Real-World Images This is the reference implementation of "Learning Generative Models of Texture

Dario Pavllo 115 Jan 07, 2023
Ladder Variational Autoencoders (LVAE) in PyTorch

Ladder Variational Autoencoders (LVAE) PyTorch implementation of Ladder Variational Autoencoders (LVAE) [1]: where the variational distributions q at

Andrea Dittadi 63 Dec 22, 2022
OCR-D wrapper for detectron2 based segmentation models

ocrd_detectron2 OCR-D wrapper for detectron2 based segmentation models Introduction Installation Usage OCR-D processor interface ocrd-detectron2-segm

Robert Sachunsky 13 Dec 06, 2022
PyTorch Implementation of NCSOFT's FastPitchFormant: Source-filter based Decomposed Modeling for Speech Synthesis

FastPitchFormant - PyTorch Implementation PyTorch Implementation of FastPitchFormant: Source-filter based Decomposed Modeling for Speech Synthesis. Qu

Keon Lee 63 Jan 02, 2023
PyTorch version repo for CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes

Study-CSRNet-pytorch This is the PyTorch version repo for CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes

0 Mar 01, 2022
Prediction of MBA refinance Index (Mortgage prepayment)

Prediction of MBA refinance Index (Mortgage prepayment) Deep Neural Network based Model The ability to predict mortgage prepayment is of critical use

Ruchil Barya 1 Jan 16, 2022
Optimized Gillespie algorithm for simulating Stochastic sPAtial models of Cancer Evolution (OG-SPACE)

OG-SPACE Introduction Optimized Gillespie algorithm for simulating Stochastic sPAtial models of Cancer Evolution (OG-SPACE) is a computational framewo

Data and Computational Biology Group UNIMIB (was BI*oinformatics MI*lan B*icocca) 0 Nov 17, 2021
BT-Unet: A-Self-supervised-learning-framework-for-biomedical-image-segmentation-using-Barlow-Twins

BT-Unet: A-Self-supervised-learning-framework-for-biomedical-image-segmentation-using-Barlow-Twins Deep learning has brought most profound contributio

Narinder Singh Punn 12 Dec 04, 2022
Codes for paper "KNAS: Green Neural Architecture Search"

KNAS Codes for paper "KNAS: Green Neural Architecture Search" KNAS is a green (energy-efficient) Neural Architecture Search (NAS) approach. It contain

90 Dec 22, 2022
ByteTrack超详细教程！训练自己的数据集&&摄像头实时检测跟踪

ByteTrack超详细教程！训练自己的数据集&&摄像头实时检测跟踪

Double-zh 45 Dec 19, 2022
Code accompanying "Evolving spiking neuron cellular automata and networks to emulate in vitro neuronal activity," accepted to IEEE SSCI ICES 2021

Evolving-spiking-neuron-cellular-automata-and-networks-to-emulate-in-vitro-neuronal-activity Code accompanying "Evolving spiking neuron cellular autom

SOCRATES: Self-Organizing Computational substRATES 2 Dec 02, 2022
Towards Representation Learning for Atmospheric Dynamics (AtmoDist)

Towards Representation Learning for Atmospheric Dynamics (AtmoDist) The prediction of future climate scenarios under anthropogenic forcing is critical

Sebastian Hoffmann 4 Dec 15, 2022
Deep Learning and Reinforcement Learning Library for Scientists and Engineers 🔥

TensorLayer is a novel TensorFlow-based deep learning and reinforcement learning library designed for researchers and engineers. It provides an extens

TensorLayer Community 7.1k Dec 27, 2022
Pytorch implementation for ACMMM2021 paper "I2V-GAN: Unpaired Infrared-to-Visible Video Translation".

I2V-GAN This repository is the official Pytorch implementation for ACMMM2021 paper "I2V-GAN: Unpaired Infrared-to-Visible Video Translation". Traffic

69 Dec 31, 2022
D-NeRF: Neural Radiance Fields for Dynamic Scenes

D-NeRF: Neural Radiance Fields for Dynamic Scenes [Project] [Paper] D-NeRF is a method for synthesizing novel views, at an arbitrary point in time, of

Albert Pumarola 291 Jan 02, 2023
TrackFormer: Multi-Object Tracking with Transformers

TrackFormer: Multi-Object Tracking with Transformers This repository provides the official implementation of the TrackFormer: Multi-Object Tracking wi

Tim Meinhardt 321 Dec 29, 2022
Good Classification Measures and How to Find Them

Good Classification Measures and How to Find Them This repository contains supplementary materials for the paper "Good Classification Measures and How

Yandex Research 7 Nov 13, 2022
A large dataset of 100k Google Satellite and matching Map images, resembling pix2pix's Google Maps dataset.

Larger Google Sat2Map dataset This dataset extends the aerial ⟷ Maps dataset used in pix2pix (Isola et al., CVPR17). The provide script download_sat2m

34 Dec 28, 2022