ReAct: Out-of-distribution Detection With Rectified Activations

Related tags

Deep Learningreact
Overview

ReAct: Out-of-distribution Detection With Rectified Activations

This is the source code for paper ReAct: Out-of-distribution Detection With Rectified Activations by Yiyou Sun, Chuan Guo and Yixuan Li.

In this work, we propose ReAct—a simple technique for reducing model overconfidence on OOD data. Our method is motivated by novel analysis on internal activations of neural networks, which displays highly distinctive signature patterns for most OOD distributions.

Usage

1. Dataset Preparation

In-distribution dataset

Please download ImageNet-1k and place the training data and validation data in ./datasets/id_data/ILSVRC-2012/train and ./datasets/id_data/ILSVRC-2012/val, respectively.

Out-of-distribution dataset

We have curated 4 OOD datasets from iNaturalist, SUN, Places, and Textures, and de-duplicated concepts overlapped with ImageNet-1k.

For iNaturalist, SUN, and Places, we have sampled 10,000 images from the selected concepts for each dataset, which can be download via the following links:

wget http://pages.cs.wisc.edu/~huangrui/imagenet_ood_dataset/iNaturalist.tar.gz
wget http://pages.cs.wisc.edu/~huangrui/imagenet_ood_dataset/SUN.tar.gz
wget http://pages.cs.wisc.edu/~huangrui/imagenet_ood_dataset/Places.tar.gz

For Textures, we use the entire dataset, which can be downloaded from their original website.

Please put all downloaded OOD datasets into ./datasets/ood_data/.

2. Pre-trained Model Preparation

The model we used in the paper is the pre-trained ResNet-50 and MobileNet-v2 provided by Pytorch. The download process will start upon running.

3. OOD Detection Evaluation

To reproduce our results on ResNet-50, please run:

python eval.py --threshold 1.0

To reproduce baseline approaches (Energy Score), please run:

python eval.py --threshold 1e6  #we set the threshold close to infinity, so it is the original energy score.

OOD Detection Results

ReACT achieves state-of-the-art performance averaged on the 4 OOD datasets.

results

Citation

If you use our codebase, please cite our work:

@inproceedings{sun2021react,
  title={ReAct: Out-of-distribution Detection With Rectified Activations},
  author={Sun, Yiyou and Guo, Chuan and Li, Yixuan},
  booktitle={Advances in Neural Information Processing Systems},
  year={2021}
}
Owner
CS Research Group led by Prof. Sharon Li
Colar: Effective and Efficient Online Action Detection by Consulting Exemplars, CVPR 2022.

Colar: Effective and Efficient Online Action Detection by Consulting Exemplars This repository is the official implementation of Colar. In this work,

LeYang 246 Dec 13, 2022
Annotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN

Overview PyTorch 0.4.1 | Python 3.6.5 Annotated implementations with comparative introductions for minimax, non-saturating, wasserstein, wasserstein g

Shayne O'Brien 471 Dec 16, 2022
Opinionated code formatter, just like Python's black code formatter but for Beancount

beancount-black Opinionated code formatter, just like Python's black code formatter but for Beancount Try it out online here Features MIT licensed - b

Launch Platform 16 Oct 11, 2022
Simple and understandable swin-transformer OCR project

swin-transformer-ocr ocr with swin-transformer Overview Simple and understandable swin-transformer OCR project. The model in this repository heavily r

Ha YongWook 67 Dec 31, 2022
Pca-on-genotypes - Mini bioinformatics project - PCA on genotypes

Mini bioinformatics project: PCA on genotypes This repo contains the code from t

Maria Nattestad 8 Dec 04, 2022
Indonesian Car License Plate Character Recognition using Tensorflow, Keras and OpenCV.

Monopol Indonesian Car License Plate (Indonesia Mobil Nomor Polisi) Character Recognition using Tensorflow, Keras and OpenCV. Background This applicat

Jayaku Briliantio 3 Apr 07, 2022
Reinforcement Learning Theory Book (rus)

Reinforcement Learning Theory Book (rus)

qbrick 206 Nov 27, 2022
Json2Xml tool will help you convert from json COCO format to VOC xml format in Object Detection Problem.

JSON 2 XML All codes assume running from root directory. Please update the sys path at the beginning of the codes before running. Over View Json2Xml t

Nguyễn Trường Lâu 6 Aug 22, 2022
Predict halo masses from simulations via graph neural networks

HaloGraphNet Predict halo masses from simulations via Graph Neural Networks. Given a dark matter halo and its galaxies, creates a graph with informati

Pablo Villanueva Domingo 20 Nov 15, 2022
Computer Vision Paper Reviews with Key Summary of paper, End to End Code Practice and Jupyter Notebook converted papers

Computer-Vision-Paper-Reviews Computer Vision Paper Reviews with Key Summary along Papers & Codes. Jonathan Choi 2021 The repository provides 100+ Pap

Jonathan Choi 2 Mar 17, 2022
PyTorch implementation of: Michieli U. and Zanuttigh P., "Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations", CVPR 2021.

Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations This is the official PyTorch implementation

Multimedia Technology and Telecommunication Lab 42 Nov 09, 2022
A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility

Tensorpack is a neural network training interface based on TensorFlow. Features: It's Yet Another TF high-level API, with speed, and flexibility built

Tensorpack 6.2k Jan 09, 2023
YOLOX-CondInst - Implement CondInst which is a instances segmentation method on YOLOX

YOLOX CondInst -- YOLOX 实例分割 前言 本项目是自己学习实例分割时,复现的代码. 通过自己编程,让自己对实例分割有更进一步的了解。 若想

DDGRCF 16 Nov 18, 2022
Novel Instances Mining with Pseudo-Margin Evaluation for Few-Shot Object Detection

Novel Instances Mining with Pseudo-Margin Evaluation for Few-Shot Object Detection (NimPme) The official implementation of Novel Instances Mining with

12 Sep 08, 2022
GRaNDPapA: Generator of Rad Names from Decent Paper Acronyms

GRaNDPapA: Generator of Rad Names from Decent Paper Acronyms Trying to publish a new machine learning model and can't write a decent title for your pa

264 Nov 08, 2022
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

DLR-RM 4.7k Jan 01, 2023
KITTI-360 Annotation Tool is a framework that developed based on python(cherrypy + jinja2 + sqlite3) as the server end and javascript + WebGL as the front end.

KITTI-360 Annotation Tool is a framework that developed based on python(cherrypy + jinja2 + sqlite3) as the server end and javascript + WebGL as the front end.

86 Dec 12, 2022
Official PyTorch implementation of Joint Object Detection and Multi-Object Tracking with Graph Neural Networks

This is the official PyTorch implementation of our paper: "Joint Object Detection and Multi-Object Tracking with Graph Neural Networks". Our project website and video demos are here.

Richard Wang 443 Dec 06, 2022
Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk

Annoy Annoy (Approximate Nearest Neighbors Oh Yeah) is a C++ library with Python bindings to search for points in space that are close to a given quer

Spotify 10.6k Jan 04, 2023
Yolo object detection - Yolo object detection with python

How to run download required files make build_image make download Docker versio

3 Jan 26, 2022