[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.
QuanTaichi evaluation suite

QuanTaichi: A Compiler for Quantized Simulations (SIGGRAPH 2021) Yuanming Hu, Jiafeng Liu, Xuanda Yang, Mingkuan Xu, Ye Kuang, Weiwei Xu, Qiang Dai, W

Taichi Developers 120 Jan 04, 2023
Official Implementation of DE-CondDETR and DELA-CondDETR in "Towards Data-Efficient Detection Transformers"

DE-DETRs By Wen Wang, Jing Zhang, Yang Cao, Yongliang Shen, and Dacheng Tao This repository is an official implementation of DE-CondDETR and DELA-Cond

Wen Wang 41 Dec 12, 2022
Classifies galaxy morphology with Bayesian CNN

Zoobot Zoobot classifies galaxy morphology with deep learning. This code will let you: Reproduce and improve the Galaxy Zoo DECaLS automated classific

Mike Walmsley 39 Dec 20, 2022
3DMV jointly combines RGB color and geometric information to perform 3D semantic segmentation of RGB-D scans.

3DMV 3DMV jointly combines RGB color and geometric information to perform 3D semantic segmentation of RGB-D scans. This work is based on our ECCV'18 p

Владислав Молодцов 0 Feb 06, 2022
Code base for "On-the-Fly Test-time Adaptation for Medical Image Segmentation"

On-the-Fly Adaptation Official Pytorch Code base for On-the-Fly Test-time Adaptation for Medical Image Segmentation Paper Introduction One major probl

Jeya Maria Jose 17 Nov 10, 2022
Submodular Subset Selection for Active Domain Adaptation (ICCV 2021)

S3VAADA: Submodular Subset Selection for Virtual Adversarial Active Domain Adaptation ICCV 2021 Harsh Rangwani, Arihant Jain*, Sumukh K Aithal*, R. Ve

Video Analytics Lab -- IISc 13 Dec 28, 2022
An ever-growing playground of notebooks showcasing CLIP's impressive zero-shot capabilities.

Playground for CLIP-like models Demo Colab Link GradCAM Visualization Naive Zero-shot Detection Smarter Zero-shot Detection Captcha Solver Changelog 2

Kevin Zakka 101 Dec 30, 2022
Mosaic of Object-centric Images as Scene-centric Images (MosaicOS) for long-tailed object detection and instance segmentation.

MosaicOS Mosaic of Object-centric Images as Scene-centric Images (MosaicOS) for long-tailed object detection and instance segmentation. Introduction M

Cheng Zhang 27 Oct 12, 2022
Deep Learning Theory

Deep Learning Theory 整理了一些深度学习的理论相关内容,持续更新。 Overview Recent advances in deep learning theory 总结了目前深度学习理论研究的六个方向的一些结果,概述型,没做深入探讨(2021)。 1.1 complexity

fq 103 Jan 04, 2023
Pytorch implementation of AREL

Status: Archive (code is provided as-is, no updates expected) Agent-Temporal Attention for Reward Redistribution in Episodic Multi-Agent Reinforcement

8 Nov 25, 2022
Codes for NeurIPS 2021 paper "Adversarial Neuron Pruning Purifies Backdoored Deep Models"

Adversarial Neuron Pruning Purifies Backdoored Deep Models Code for NeurIPS 2021 "Adversarial Neuron Pruning Purifies Backdoored Deep Models" by Dongx

Dongxian Wu 31 Dec 11, 2022
Prototypical python implementation of the trust-region algorithm presented in Sequential Linearization Method for Bound-Constrained Mathematical Programs with Complementarity Constraints by Larson, Leyffer, Kirches, and Manns.

Prototypical python implementation of the trust-region algorithm presented in Sequential Linearization Method for Bound-Constrained Mathematical Programs with Complementarity Constraints by Larson, L

3 Dec 02, 2022
Source Code of NeurIPS21 paper: Recognizing Vector Graphics without Rasterization

YOLaT-VectorGraphicsRecognition This repository is the official PyTorch implementation of our NeurIPS-2021 paper: Recognizing Vector Graphics without

Microsoft 49 Dec 20, 2022
FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.

Detectron is deprecated. Please see detectron2, a ground-up rewrite of Detectron in PyTorch. Detectron Detectron is Facebook AI Research's software sy

Facebook Research 25.5k Jan 07, 2023
PyTorch implementations of Generative Adversarial Networks.

This repository has gone stale as I unfortunately do not have the time to maintain it anymore. If you would like to continue the development of it as

Erik Linder-Norén 13.4k Jan 08, 2023
Official Code for VideoLT: Large-scale Long-tailed Video Recognition (ICCV 2021)

Pytorch Code for VideoLT [Website][Paper] Updates [10/29/2021] Features uploaded to Google Drive, for access please send us an e-mail: zhangxing18 at

Skye 26 Sep 18, 2022
Video Instance Segmentation with a Propose-Reduce Paradigm (ICCV 2021)

Propose-Reduce VIS This repo contains the official implementation for the paper: Video Instance Segmentation with a Propose-Reduce Paradigm Huaijia Li

DV Lab 39 Nov 23, 2022
Code for KHGT model, AAAI2021

KHGT Code for KHGT accepted by AAAI2021 Please unzip the data files in Datasets/ first. To run KHGT on Yelp data, use python labcode_yelp.py For Movi

32 Nov 29, 2022
Bravia core script for python

Bravia-Core-Script You need to have a mandatory account If this L3 does not work, try another L3. enjoy

5 Dec 26, 2021
Unofficial implementation of "TTNet: Real-time temporal and spatial video analysis of table tennis" (CVPR 2020)

TTNet-Pytorch The implementation for the paper "TTNet: Real-time temporal and spatial video analysis of table tennis" An introduction of the project c

Nguyen Mau Dung 438 Dec 29, 2022