Towards Calibrated Model for Long-Tailed Visual Recognition from Prior Perspective

Related tags

Deep LearningPrior-LT
Overview

Towards Calibrated Model for Long-Tailed Visual Recognition from Prior Perspective

Zhengzhuo Xu, Zenghao Chai, Chun Yuan


This is the PyTorch implementation of our paper in NeurIPS 2021.

Environment settings

  • PyTorch >= 1.4
  • Scikit-learn
  • Matplotlib

Training

To train the model, please select a config file path or customize by yourself. For example:

python train.py ./config/cifar10_100.py

The result will be saved in ./result.

Inferance model

Dataset log Model
CIFAR-10-LT-50 link link
CIFAR-10-LT-100 link link
CIFAR-10-LT-200 link link
CIFAR-100-LT-50 link link
CIFAR-100-LT-100 link link
CIFAR-100-LT-200 link link

Note

  • Some settings may be a little different from the paper reported. Because we make further optimization considering reviewers' suggestions.
  • Some bugs need to be fixed when imb factor = 0.1
  • Need to solve the test-agnostic situation.

Reference

Welcome to cite:

@inproceedings{
xu2021towards,
title={Towards Calibrated Model for Long-Tailed Visual Recognition from Prior Perspective},
author={Zhengzhuo Xu and Zenghao Chai and Chun Yuan},
booktitle={Thirty-Fifth Conference on Neural Information Processing Systems},
year={2021},
url={https://openreview.net/forum?id=vqzAfN-BoA_}
}

Acknowledgement

We adopt the code from the following repos. We thank them for providing their awesome code.

Owner
Sincere
Wait, let me code a bug first ...
Sincere
A standard framework for modelling Deep Learning Models for tabular data

PyTorch Tabular aims to make Deep Learning with Tabular data easy and accessible to real-world cases and research alike.

801 Jan 08, 2023
Epidemiology analysis package

zEpid zEpid is an epidemiology analysis package, providing easy to use tools for epidemiologists coding in Python 3.5+. The purpose of this library is

Paul Zivich 111 Jan 08, 2023
Pure python implementations of popular ML algorithms.

Minimal ML algorithms This repo includes minimal implementations of popular ML algorithms using pure python and numpy. The purpose of these notebooks

Alexis Gidiotis 3 Jan 10, 2022
A module that used for encrypt code which includes RSA and AES

软件加密模块 requirement: Crypto,pycryptodome,pyqt5 本地加密信息为随机字符串 使用说明 命令行参数 -h 帮助 -checkWorking 检查是否能正常工作,后接1确认指令 -checkEndDate 检查截至日期,后接1确认指令 -activateCode

2 Sep 27, 2022
A complete, self-contained example for training ImageNet at state-of-the-art speed with FFCV

ffcv ImageNet Training A minimal, single-file PyTorch ImageNet training script designed for hackability. Run train_imagenet.py to get... ...high accur

FFCV 92 Dec 31, 2022
Semi-supervised Implicit Scene Completion from Sparse LiDAR

Semi-supervised Implicit Scene Completion from Sparse LiDAR Paper Created by Pengfei Li, Yongliang Shi, Tianyu Liu, Hao Zhao, Guyue Zhou and YA-QIN ZH

114 Nov 30, 2022
Manipulation OpenAI Gym environments to simulate robots at the STARS lab

Manipulator Learning This repository contains a set of manipulation environments that are compatible with OpenAI Gym and simulated in pybullet. In par

STARS Laboratory 5 Dec 08, 2022
exponential adaptive pooling for PyTorch

AdaPool: Exponential Adaptive Pooling for Information-Retaining Downsampling Abstract Pooling layers are essential building blocks of Convolutional Ne

Alexandros Stergiou 55 Jan 04, 2023
An implementation of a sequence to sequence neural network using an encoder-decoder

Keras implementation of a sequence to sequence model for time series prediction using an encoder-decoder architecture. I created this post to share a

Luke Tonin 195 Dec 17, 2022
A Simple LSTM-Based Solution for "Heartbeat Signal Classification and Prediction" in Tianchi

LSTM-Time-Series-Prediction A Simple LSTM-Based Solution for "Heartbeat Signal Classification and Prediction" in Tianchi Contest. The Link of the Cont

KevinCHEN 1 Jun 13, 2022
Official code for paper "ISNet: Costless and Implicit Image Segmentation for Deep Classifiers, with Application in COVID-19 Detection"

Official code for paper "ISNet: Costless and Implicit Image Segmentation for Deep Classifiers, with Application in COVID-19 Detection". LRPDenseNet.py

Pedro Ricardo Ariel Salvador Bassi 2 Sep 21, 2022
NeuroGen: activation optimized image synthesis for discovery neuroscience

NeuroGen: activation optimized image synthesis for discovery neuroscience NeuroGen is a framework for synthesizing images that control brain activatio

3 Aug 17, 2022
code for "Self-supervised edge features for improved Graph Neural Network training",

Self-supervised edge features for improved Graph Neural Network training Data availability: Here is a link to the raw data for the organoids dataset.

Neal Ravindra 23 Dec 02, 2022
Supervised 3D Pre-training on Large-scale 2D Natural Image Datasets for 3D Medical Image Analysis

Introduction This is an implementation of our paper Supervised 3D Pre-training on Large-scale 2D Natural Image Datasets for 3D Medical Image Analysis.

24 Dec 06, 2022
Hl classification bc - A Network-Based High-Level Data Classification Algorithm Using Betweenness Centrality

A Network-Based High-Level Data Classification Algorithm Using Betweenness Centr

Esteban Vilca 3 Dec 01, 2022
PyTorch implementation of image classification models for CIFAR-10/CIFAR-100/MNIST/FashionMNIST/Kuzushiji-MNIST/ImageNet

PyTorch Image Classification Following papers are implemented using PyTorch. ResNet (1512.03385) ResNet-preact (1603.05027) WRN (1605.07146) DenseNet

1.2k Jan 04, 2023
Flexible Networks for Learning Physical Dynamics of Deformable Objects (2021)

Flexible Networks for Learning Physical Dynamics of Deformable Objects (2021) By Jinhyung Park, Dohae Lee, In-Kwon Lee from Yonsei University (Seoul,

Jinhyung Park 0 Jan 09, 2022
A highly efficient and modular implementation of Gaussian Processes in PyTorch

GPyTorch GPyTorch is a Gaussian process library implemented using PyTorch. GPyTorch is designed for creating scalable, flexible, and modular Gaussian

3k Jan 02, 2023
TriMap: Large-scale Dimensionality Reduction Using Triplets

TriMap TriMap is a dimensionality reduction method that uses triplet constraints to form a low-dimensional embedding of a set of points. The triplet c

Ehsan Amid 235 Dec 24, 2022
A Lightweight Hyperparameter Optimization Tool 🚀

Lightweight Hyperparameter Optimization 🚀 The mle-hyperopt package provides a simple and intuitive API for hyperparameter optimization of your Machin

136 Jan 08, 2023