Code of Adverse Weather Image Translation with Asymmetric and Uncertainty aware GAN

Related tags

Deep LearningAU-GAN
Overview

Adverse Weather Image Translation with Asymmetric and Uncertainty-aware GAN (AU-GAN)

Official Tensorflow implementation of Adverse Weather Image Translation with Asymmetric and Uncertainty-aware GAN (AU-GAN)
Jeong-gi Kwak, Youngsaeng Jin, Yuanming Li, Dongsik Yoon, Donghyeon Kim and Hanseok Ko
British Machine Vision Conference (BMVC), 2021

Intro

Night → Day (BDD100K)

Rainy night → Day (Alderdey)


Architecture

Our generator has asymmetric structure for editing day→night and night→day. Please refer our paper for details

Envs

git clone https://github.com/jgkwak95/AU-GAN.git
cd AU-GAN

# Create virtual environment
conda create -y --name augan python=3.6.7
conda activate augan

conda install tensorflow-gpu==1.14.0   # Tensorflow 1.14
pip install --no-cache-dir -r requirements.txt

Preparing datasets

Night → Day
Berkeley DeepDrive dataset contains 100,000 high resolution images of the urban roads for autonomous driving.

Rainy night → Day
Alderley dataset consists of images of two domains, rainy night and daytime. It was collected while driving the same route in each weather environment.

Please download datasets and then construct them following ForkGAN

Training

# Alderley (256x256)
python main_uncer.py --dataset_dir alderley
                     --phase train
                     --experiment_name alderley_exp
                     --batch_size 8 
                     --load_size 286 
                     --fine_size 256 
                     --use_uncertainty True
# BDD100k (512x512)
python main_uncer.py --dataset_dir bdd100k 
                     --phase train
                     --experiment_name bdd_exp
                     --batch_size 4 
                     --load_size 572 
                     --fine_size 512 
                     --use_uncertainty True

Test

# Alderley (256x256)
python main_uncer.py --dataset_dir alderley
                     --phase test
                     --experiment_name alderley_exp
                     --batch_size 1 
                     --load_size 286 
                     --fine_size 256 
                    
# BDD100k (512x512)
python main_uncer.py --dataset_dir bdd100k
                     --phase test
                     --experiment_name bdd_exp
                     --batch_size 1 
                     --load_size 572 
                     --fine_size 512 
                    

Additional results

More results in paper and supplementary

Uncertainty map

Citation

If our code is helpful your research, please cite our paper:

@InProceedings{kwak_adverse_2021},
  author = {Kwak, Jeong-gi and Jin, Youngsaeng and Li, Yuanming and Yoon, Dongsik and Kim, Donghyeon and Ko, Hanseok},
  title = {Adverse Weather Image Translation with Asymmetric and Uncertainty-aware GAN},
  booktitle = {British Conference of Computer Vision (BMVC)},
  month = {November},
  year = {2021}
}

Acknowledgments

Our code is bulided upon the ForkGAN implementation.

Owner
Jeong-gi Kwak
Jeong-gi Kwak
The repository offers the official implementation of our BMVC 2021 paper in PyTorch.

CrossMLP Cascaded Cross MLP-Mixer GANs for Cross-View Image Translation Bin Ren1, Hao Tang2, Nicu Sebe1. 1University of Trento, Italy, 2ETH, Switzerla

Bingoren 16 Jul 27, 2022
Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai

Coursera-deep-learning-specialization - Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks an

Aman Chadha 1.7k Jan 08, 2023
TFOD-MASKRCNN - Tensorflow MaskRCNN With Python

Tensorflow- MaskRCNN Steps git clone https://github.com/amalaj7/TFOD-MASKRCNN.gi

Amal Ajay 2 Jan 18, 2022
TensorFlow implementation of "Attention is all you need (Transformer)"

[TensorFlow 2] Attention is all you need (Transformer) TensorFlow implementation of "Attention is all you need (Transformer)" Dataset The MNIST datase

YeongHyeon Park 4 Jan 05, 2022
A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.

Telemanom (v2.0) v2.0 updates: Vectorized operations via numpy Object-oriented restructure, improved organization Merge branches into single branch fo

Kyle Hundman 844 Dec 28, 2022
Code repo for "Cross-Scale Internal Graph Neural Network for Image Super-Resolution" (NeurIPS'20)

IGNN Code repo for "Cross-Scale Internal Graph Neural Network for Image Super-Resolution" [paper] [supp] Prepare datasets 1 Download training dataset

Shangchen Zhou 278 Jan 03, 2023
Personal implementation of paper "Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval"

Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval This repo provides personal implementation of paper Approximate Ne

John 8 Oct 07, 2022
This respository includes implementations on Manifoldron: Direct Space Partition via Manifold Discovery

Manifoldron: Direct Space Partition via Manifold Discovery This respository includes implementations on Manifoldron: Direct Space Partition via Manifo

dayang_wang 4 Apr 28, 2022
MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from a Single Moving Camera

MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from a Single Moving Camera

Felix Wimbauer 494 Jan 06, 2023
This is an official repository of CLGo: Learning to Predict 3D Lane Shape and Camera Pose from a Single Image via Geometry Constraints

CLGo This is an official repository of CLGo: Learning to Predict 3D Lane Shape and Camera Pose from a Single Image via Geometry Constraints An earlier

刘芮金 32 Dec 20, 2022
Collections for the lasted paper about multi-view clustering methods (papers, codes)

Multi-View Clustering Papers Collections for the lasted paper about multi-view clustering methods (papers, codes). There also exists some repositories

Andrew Guan 10 Sep 20, 2022
Efficiently computes derivatives of numpy code.

Note: Autograd is still being maintained but is no longer actively developed. The main developers (Dougal Maclaurin, David Duvenaud, Matt Johnson, and

Formerly: Harvard Intelligent Probabilistic Systems Group -- Now at Princeton 6.1k Jan 08, 2023
Semantic Edge Detection with Diverse Deep Supervision

Semantic Edge Detection with Diverse Deep Supervision This repository contains the code for our IJCV paper: "Semantic Edge Detection with Diverse Deep

Yun Liu 12 Dec 31, 2022
Multi-Horizon-Forecasting-for-Limit-Order-Books

Multi-Horizon-Forecasting-for-Limit-Order-Books This jupyter notebook is used to demonstrate our work, Multi-Horizon Forecasting for Limit Order Books

Zihao Zhang 116 Dec 23, 2022
Official code implementation for "Personalized Federated Learning using Hypernetworks"

Personalized Federated Learning using Hypernetworks This is an official implementation of Personalized Federated Learning using Hypernetworks paper. [

Aviv Shamsian 121 Dec 25, 2022
The code for paper "Contrastive Spatio-Temporal Pretext Learning for Self-supervised Video Representation" which is accepted by AAAI 2022

Contrastive Spatio Temporal Pretext Learning for Self-supervised Video Representation (AAAI 2022) The code for paper "Contrastive Spatio-Temporal Pret

8 Jun 30, 2022
RaceBERT -- A transformer based model to predict race and ethnicty from names

RaceBERT -- A transformer based model to predict race and ethnicty from names Installation pip install racebert Using a virtual environment is highly

Prasanna Parasurama 3 Nov 02, 2022
OpenGAN: Open-Set Recognition via Open Data Generation

OpenGAN: Open-Set Recognition via Open Data Generation ICCV 2021 (oral) Real-world machine learning systems need to analyze novel testing data that di

Shu Kong 90 Jan 06, 2023
A hybrid SOTA solution of LiDAR panoptic segmentation with C++ implementations of point cloud clustering algorithms. ICCV21, Workshop on Traditional Computer Vision in the Age of Deep Learning

ICCVW21-TradiCV-Survey-of-LiDAR-Cluster Motivation In contrast to popular end-to-end deep learning LiDAR panoptic segmentation solutions, we propose a

YimingZhao 103 Nov 22, 2022
A neuroanatomy-based augmented reality experience powered by computer vision. Features 3D visuals of the Atlas Brain Map slices.

Brain Augmented Reality (AR) A neuroanatomy-based augmented reality experience powered by computer vision that features 3D visuals of the Atlas Brain

Yasmeen Brain 10 Oct 06, 2022