[ICML'21] Estimate the accuracy of the classifier in various environments through self-supervision

Overview

What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments?

[Paper] [ICML'21 Project]

PyTorch Implementation

This repository contains:

  • the PyTorch implementation of AutoEavl.
  • the example on CIFAR-10 setup (use imgaug)
  • linear regression

Please follow the instruction below to install it and run the experiment demo.

Prerequisites

  • Linux (tested on Ubuntu 16.04LTS)
  • NVIDIA GPU + CUDA CuDNN (tested on GTX 2080 Ti)
  • CIFAR-10 (download and unzip to PROJECT_DIR/data/)
  • CIFAR10.1 (download and unzip to PROJECT_DIR/data/CIFAR-10.1)
  • Please use PyTorch1.5 to avoid compilation errors (other versions should be good)
  • You might need to change the file paths, and please be sure you change the corresponding paths in the codes as well

Getting started

  1. Install dependencies
    # Imgaug (or see https://imgaug.readthedocs.io/en/latest/source/installation.html)
    conda config --add channels conda-forge
    conda install imgaug
  2. Creat synthetic sets
    # By default it creates 500 synthetic sets
    python generate_synthetic_sets.py
  3. Learn classifier on CIFAR-10 (DenseNet-10-12)
    # Save as "PROJECT_DIR/DenseNet-40-12-ss/checkpoint.pth.tar"
    # Modified based on the wonderful github of https://github.com/andreasveit/densenet-pytorch
    python train.py --layers 40 --growth 12 --no-bottleneck --reduce 1.0
  4. Test classifier on synthetic sets
    # 1) Get "PROJECT_DIR/accuracy_cls_dense_aug.npy" file
    # 2) Get "PROJECT_DIR/accuracy_ss_dense_aug.npy" file
    # 3) You will see Rank correlation and Pearsons correlation
    # 4) The absolute error of linear regression is also shown
    python test_many.py --layers 40 --growth 12 --no-bottleneck --reduce 1.0
  5. Correlation study
    # You will see correlation.pdf;
    python analyze_correlation.py
        

Citation

If you use the code in your research, please cite:

    @inproceedings{Deng:ICML2021,
      author    = {Weijian Deng and
                   Stephen Gould and
                   Liang Zheng},
      title     = {What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments?},
      booktitle = {ICML},
      year      = {2021}
    }

License

MIT

Owner
Third-year PhD student at ANU.
Image-to-image translation with conditional adversarial nets

pix2pix Project | Arxiv | PyTorch Torch implementation for learning a mapping from input images to output images, for example: Image-to-Image Translat

Phillip Isola 9.3k Jan 08, 2023
A Topic Modeling toolbox

Topik A Topic Modeling toolbox. Introduction The aim of topik is to provide a full suite and high-level interface for anyone interested in applying to

Anaconda, Inc. (formerly Continuum Analytics, Inc.) 93 Dec 01, 2022
Public Implementation of ChIRo from "Learning 3D Representations of Molecular Chirality with Invariance to Bond Rotations"

Learning 3D Representations of Molecular Chirality with Invariance to Bond Rotations This directory contains the model architectures and experimental

35 Dec 05, 2022
Tilted Empirical Risk Minimization (ICLR '21)

Tilted Empirical Risk Minimization This repository contains the implementation for the paper Tilted Empirical Risk Minimization ICLR 2021 Empirical ri

Tian Li 40 Nov 28, 2022
TorchOk - The toolkit for fast Deep Learning experiments in Computer Vision

TorchOk - The toolkit for fast Deep Learning experiments in Computer Vision

52 Dec 23, 2022
python library for invisible image watermark (blind image watermark)

invisible-watermark invisible-watermark is a python library and command line tool for creating invisible watermark over image.(aka. blink image waterm

Shield Mountain 572 Jan 07, 2023
Pytorch implementation of Learning with Opponent-Learning Awareness

Pytorch implementation of Learning with Opponent-Learning Awareness using DiCE

Alexis David Jacq 82 Sep 15, 2022
Author: Wenhao Yu ([email protected]). ACL 2022. Commonsense Reasoning on Knowledge Graph for Text Generation

Diversifying Commonsense Reasoning Generation on Knowledge Graph Introduction -- This is the pytorch implementation of our ACL 2022 paper "Diversifyin

DM2 Lab @ ND 61 Dec 30, 2022
Autoregressive Predictive Coding: An unsupervised autoregressive model for speech representation learning

Autoregressive Predictive Coding This repository contains the official implementation (in PyTorch) of Autoregressive Predictive Coding (APC) proposed

iamyuanchung 173 Dec 18, 2022
A Model for Natural Language Attack on Text Classification and Inference

TextFooler A Model for Natural Language Attack on Text Classification and Inference This is the source code for the paper: Jin, Di, et al. "Is BERT Re

Di Jin 418 Dec 16, 2022
This repository is maintained for the scientific paper tittled " Study of keyword extraction techniques for Electric Double Layer Capacitor domain using text similarity indexes: An experimental analysis "

kwd-extraction-study This repository is maintained for the scientific paper tittled " Study of keyword extraction techniques for Electric Double Layer

ping 543f 1 Dec 05, 2022
Implementation for "Conditional entropy minimization principle for learning domain invariant representation features"

Implementation for "Conditional entropy minimization principle for learning domain invariant representation features". The code is reproduced from thi

1 Nov 02, 2022
From this paper "SESNet: A Semantically Enhanced Siamese Network for Remote Sensing Change Detection"

SESNet for remote sensing image change detection It is the implementation of the paper: "SESNet: A Semantically Enhanced Siamese Network for Remote Se

1 May 24, 2022
On-device wake word detection powered by deep learning.

Porcupine Made in Vancouver, Canada by Picovoice Porcupine is a highly-accurate and lightweight wake word engine. It enables building always-listening

Picovoice 2.8k Dec 29, 2022
This is the pytorch implementation for the paper: *Learning Accurate Performance Predictors for Ultrafast Automated Model Compression*, which is in submission to TPAMI

SeerNet This is the pytorch implementation for the paper: Learning Accurate Performance Predictors for Ultrafast Automated Model Compression, which is

3 May 01, 2022
3D dataset of humans Manipulating Objects in-the-Wild (MOW)

MOW dataset [Website] This repository maintains our 3D dataset of humans Manipulating Objects in-the-Wild (MOW). The dataset contains 512 images in th

Zhe Cao 28 Nov 06, 2022
Official repository of "BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and Alignment"

BasicVSR_PlusPlus (CVPR 2022) [Paper] [Project Page] [Code] This is the official repository for BasicVSR++. Please feel free to raise issue related to

Kelvin C.K. Chan 227 Jan 01, 2023
Active Offline Policy Selection With Python

Active Offline Policy Selection This is supporting example code for NeurIPS 2021 paper Active Offline Policy Selection by Ksenia Konyushkova*, Yutian

DeepMind 27 Oct 15, 2022
Regularizing Nighttime Weirdness: Efficient Self-supervised Monocular Depth Estimation in the Dark (ICCV 2021)

Regularizing Nighttime Weirdness: Efficient Self-supervised Monocular Depth Estimation in the Dark (ICCV 2021) Kun Wang, Zhenyu Zhang, Zhiqiang Yan, X

kunwang 66 Nov 24, 2022
Warning: This project does not have any current developer. See bellow.

Pylearn2: A machine learning research library Warning : This project does not have any current developer. We will continue to review pull requests and

Laboratoire d’Informatique des Systèmes Adaptatifs 2.7k Dec 26, 2022