Code from PropMix, accepted at BMVC'21

Related tags

Deep LearningPropMix
Overview

PropMix: Hard Sample Filtering and Proportional MixUp for Learning with Noisy Labels

This repository is the official implementation of Hard Sample Filtering and Proportional MixUp for Learning with Noisy Labels (BMVC 2021).

Authors: Filipe R. Cordeiro; Vasileios Belagiannis, Ian Reid and Gustavo Carneiro

Illustration

Requirements

  • This codebase is written for python3.
  • To install necessary python packages, run pip install -r requirements.txt.

Training and Evaluating

The pipeline for training with PropMix is the following:

  1. Self-supervised pretrain.

In our paper we use SimCLR for most of the datasets. We use moco-v2 to pre-train an InceptionResNetV2 on Webvision. Other self-supervised methods can be used as well.

If you use SimCLR, run:

python simclr.py --config_env configs/env.yml --config_exp configs/pretext/<config_file.yml> --cudaid 0

  1. Clustering

python scan.py --config_env configs/env.yml --config_exp configs/scan/<config_file.yml> --cudaid 0

  1. Train the model (using the pretraining from steps 1 and 2)

For CIFAR-10/CIFAR-100:

python propmix.py --r [0.2/0.5/0.8/0.9] --noise_mode [sym/asym] --config_env configs/env.yml --config_exp configs/propmix/<config_file.yml> --cudaid 0

Add --nopt if you wish to train from scratch, without the self-supervised pretrain, from steps 1 and 2. Add --strong_aug to use strong augmentation. Recommended for high noise rates.

License and Contributing

  • This README is formatted based on paperswithcode.
  • This project is licensed under the terms of the MIT license.
  • Feel free to post issues via Github.

Cite PropMix
If you find the code useful in your research, please consider citing our paper:

@article{cordeiroPropMix2021,
  title={PropMix: Hard Sample Filtering and Proportional MixUp for Learning with Noisy Labels},
  author={Cordeiro, F. R. and Belagiannis, Vasileios and Reid, Ian and Carneiro, Gustavo},
  journal={The 32nd British Machine Vision Conference},
  volume={?},
  year={2021}
}

Contact

Please contact [email protected] if you have any question on the codes.

KE-Dialogue: Injecting knowledge graph into a fully end-to-end dialogue system.

Learning Knowledge Bases with Parameters for Task-Oriented Dialogue Systems This is the implementation of the paper: Learning Knowledge Bases with Par

CAiRE 42 Nov 10, 2022
CIFAR-10_train-test - training and testing codes for dataset CIFAR-10

CIFAR-10_train-test - training and testing codes for dataset CIFAR-10

Frederick Wang 3 Apr 26, 2022
Fast algorithms to compute an approximation of the minimal volume oriented bounding box of a point cloud in 3D.

ApproxMVBB Status Build UnitTests Homepage Fast algorithms to compute an approximation of the minimal volume oriented bounding box of a point cloud in

Gabriel Nützi 390 Dec 31, 2022
Deep Ensemble Learning with Jet-Like architecture

Ransomware analysis using DEL with jet-like architecture comprising two CNN wings, a sparse AE tail, a non-linear PCA to produce a diverse feature space, and an MLP nose

Ahsen Nazir 2 Feb 06, 2022
Official Pytorch implementation for video neural representation (NeRV)

NeRV: Neural Representations for Videos (NeurIPS 2021) Project Page | Paper | UVG Data Hao Chen, Bo He, Hanyu Wang, Yixuan Ren, Ser-Nam Lim, Abhinav S

hao 214 Dec 28, 2022
PyJokes - Joking around with Python library pyjokes

Hi, it's Muhaimin again 👋 This is something unorthodox but cool. Don't forget t

Muhaimin A. Salay Kanton 1 Feb 02, 2022
領域を指定し、キーを入力することで画像を保存するツールです。クラス分類用のデータセット作成を想定しています。

image-capture-class-annotation 領域を指定し、キーを入力することで画像を保存するツールです。 クラス分類用のデータセット作成を想定しています。 Requirement OpenCV 3.4.2 or later Usage 実行方法は以下です。 起動後はマウスクリック4

KazuhitoTakahashi 5 May 28, 2021
Code for NeurIPS2021 submission "A Surrogate Objective Framework for Prediction+Programming with Soft Constraints"

This repository is the code for NeurIPS 2021 submission "A Surrogate Objective Framework for Prediction+Programming with Soft Constraints". Edit 2021/

10 Dec 20, 2022
All supplementary material used by me while TA-ing CS3244: Machine Learning

CS3244-Tutorial-Material All supplementary material used by me while TA-ing CS3244: Machine Learning at NUS School of Computing. What is this? I teach

Rishabh Anand 18 Sep 23, 2022
The 7th edition of NTIRE: New Trends in Image Restoration and Enhancement workshop will be held on June 2022 in conjunction with CVPR 2022.

NTIRE 2022 - Image Inpainting Challenge Important dates 2022.02.01: Release of train data (input and output images) and validation data (only input) 2

Andrés Romero 37 Nov 27, 2022
Structural Constraints on Information Content in Human Brain States

Structural Constraints on Information Content in Human Brain States Code accompanying the paper "The information content of brain states is explained

Leon Weninger 3 Sep 07, 2022
SMIS - Semantically Multi-modal Image Synthesis(CVPR 2020)

Semantically Multi-modal Image Synthesis Project page / Paper / Demo Semantically Multi-modal Image Synthesis(CVPR2020). Zhen Zhu, Zhiliang Xu, Anshen

316 Dec 01, 2022
Reading list for research topics in Masked Image Modeling

awesome-MIM Reading list for research topics in Masked Image Modeling(MIM). We list the most popular methods for MIM, if I missed something, please su

ligang 231 Dec 07, 2022
Implementation of SegNet: A Deep Convolutional Encoder-Decoder Architecture for Semantic Pixel-Wise Labelling

Caffe SegNet This is a modified version of Caffe which supports the SegNet architecture As described in SegNet: A Deep Convolutional Encoder-Decoder A

Alex Kendall 1.1k Jan 02, 2023
Libraries, tools and tasks created and used at DeepMind Robotics.

Libraries, tools and tasks created and used at DeepMind Robotics.

DeepMind 270 Nov 30, 2022
Revitalizing CNN Attention via Transformers in Self-Supervised Visual Representation Learning

Revitalizing CNN Attention via Transformers in Self-Supervised Visual Representation Learning This repository is the official implementation of CARE.

ChongjianGE 89 Dec 02, 2022
Implementation of Enformer, Deepmind's attention network for predicting gene expression, in Pytorch

Enformer - Pytorch (wip) Implementation of Enformer, Deepmind's attention network for predicting gene expression, in Pytorch. The original tensorflow

Phil Wang 235 Dec 27, 2022
Repository for "Improving evidential deep learning via multi-task learning," published in AAAI2022

Improving evidential deep learning via multi task learning It is a repository of AAAI2022 paper, “Improving evidential deep learning via multi-task le

deargen 11 Nov 19, 2022
Multi-View Consistent Generative Adversarial Networks for 3D-aware Image Synthesis (CVPR2022)

Multi-View Consistent Generative Adversarial Networks for 3D-aware Image Synthesis Multi-View Consistent Generative Adversarial Networks for 3D-aware

Xuanmeng Zhang 78 Dec 10, 2022
This is the official code release for the paper Shape and Material Capture at Home

This is the official code release for the paper Shape and Material Capture at Home. The code enables you to reconstruct a 3D mesh and Cook-Torrance BRDF from one or more images captured with a flashl

89 Dec 10, 2022