(CVPR2021) DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic Segmentation

Related tags

Deep LearningDANNet
Overview

DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic Segmentation

CVPR2021(oral) [arxiv] Framework

Requirements

  • python3.7
  • pytorch==1.5.0
  • cuda10.2

Datasets

Cityscapes: Please follow the instructions in Cityscape to download the training set.

Dark-Zurich: Please follow the instructions in Dark-Zurich to download the training/val/test set.

Testing

If needed, please directly download the visualization results of our method for Dark-zurich-val and Dark-zurich-test. Framework To reproduce the reported results in our paper (on Dark-Zurich val), please follow these steps:

Step1: download the [trained models](https://www.dropbox.com/s/fmlq806p2wqf311/trained_models.zip?dl=0) and put it in the root.
Step2: change the data and model paths in configs/test_config.py
Step3: run "python evaluation.py"
Step4: run "python compute_iou.py"

If you want to evaluate your methods on the test set, please visit this challenge for more details.

Training

If you want to train your own models, please follow these steps:

Step1: download the [pre-trained models](https://www.dropbox.com/s/3n1212kxuv82uua/pretrained_models.zip?dl=0) and put it in the root.
Step2: change the data and model paths in configs/train_config.py
Step3: run "python train.py"

Acknowledgments

The code is based on AdaptSegNet, PSPNet, Deeplab-v2 and RefineNet.

Related works

Citation

If you think this paper is useful for your research, please cite our paper:

@InProceedings{WU_2021_CVPR,
author = {Wu, Xinyi and Wu, Zhenyao and Guo, Hao and Ju, Lili and Wang, Song},
title = {DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic Segmentation},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2021}
}

Contact

Owner
W-zx-Y
W-zx-Y
We utilize deep reinforcement learning to obtain favorable trajectories for visual-inertial system calibration.

Unified Data Collection for Visual-Inertial Calibration via Deep Reinforcement Learning Update: The lastest code will be updated in this branch. Pleas

ETHZ ASL 27 Dec 29, 2022
Official code repository for "Exploring Neural Models for Query-Focused Summarization"

Query-Focused Summarization Official code repository for "Exploring Neural Models for Query-Focused Summarization" This is a work in progress. Expect

Salesforce 29 Dec 18, 2022
DCGAN-tensorflow - A tensorflow implementation of Deep Convolutional Generative Adversarial Networks

DCGAN in Tensorflow Tensorflow implementation of Deep Convolutional Generative Adversarial Networks which is a stabilize Generative Adversarial Networ

Taehoon Kim 7.1k Dec 29, 2022
A library of multi-agent reinforcement learning components and systems

Mava: a research framework for distributed multi-agent reinforcement learning Table of Contents Overview Getting Started Supported Environments System

InstaDeep Ltd 463 Dec 23, 2022
EsViT: Efficient self-supervised Vision Transformers

Efficient Self-Supervised Vision Transformers (EsViT) PyTorch implementation for EsViT, built with two techniques: A multi-stage Transformer architect

Microsoft 352 Dec 25, 2022
The Python3 import playground

The Python3 import playground I have been confused about python modules and packages, this text tries to clear the topic up a bit. Sources: https://ch

Michael Moser 5 Feb 22, 2022
Fully Convlutional Neural Networks for state-of-the-art time series classification

Deep Learning for Time Series Classification As the simplest type of time series data, univariate time series provides a reasonably good starting poin

Stephen 572 Dec 23, 2022
A library that can print Python objects in human readable format

objprint A library that can print Python objects in human readable format Install pip install objprint Usage op Use op() (or objprint()) to print obj

319 Dec 25, 2022
Taming Transformers for High-Resolution Image Synthesis

Taming Transformers for High-Resolution Image Synthesis CVPR 2021 (Oral) Taming Transformers for High-Resolution Image Synthesis Patrick Esser*, Robin

CompVis Heidelberg 3.5k Jan 03, 2023
[NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods

Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods Large Scale Learning on Non-Homophilous Graphs: New Benchmark

60 Jan 03, 2023
Dense Prediction Transformers

Vision Transformers for Dense Prediction This repository contains code and models for our paper: Vision Transformers for Dense Prediction René Ranftl,

Intelligent Systems Lab Org 1.3k Jan 02, 2023
Este conversor criará a medida exata para sua receita de capuccino gelado da grandiosa Rafaella Ballerini!

ConversorDeMedidas_CapuccinoGelado Este conversor criará a medida exata para sua receita de capuccino gelado da grandiosa Rafaella Ballerini! Requirem

Arthur Ottoni Ribeiro 48 Nov 15, 2022
Unsupervised Discovery of Object Radiance Fields

Unsupervised Discovery of Object Radiance Fields by Hong-Xing Yu, Leonidas J. Guibas and Jiajun Wu from Stanford University. arXiv link: https://arxiv

Hong-Xing Yu 148 Nov 30, 2022
Public Code for NIPS submission SimiGrad: Fine-Grained Adaptive Batching for Large ScaleTraining using Gradient Similarity Measurement

Public code for NIPS submission "SimiGrad: Fine-Grained Adaptive Batching for Large Scale Training using Gradient Similarity Measurement" This repo co

Heyang Qin 0 Oct 13, 2021
Official implementation of the ICCV 2021 paper: "The Power of Points for Modeling Humans in Clothing".

The Power of Points for Modeling Humans in Clothing (ICCV 2021) This repository contains the official PyTorch implementation of the ICCV 2021 paper: T

Qianli Ma 158 Nov 24, 2022
Informal Persian Universal Dependency Treebank

Informal Persian Universal Dependency Treebank (iPerUDT) Informal Persian Universal Dependency Treebank, consisting of 3000 sentences and 54,904 token

Roya Kabiri 0 Jan 05, 2022
Probabilistic Programming and Statistical Inference in PyTorch

PtStat Probabilistic Programming and Statistical Inference in PyTorch. Introduction This project is being developed during my time at Cogent Labs. The

Stefano Peluchetti 109 Nov 26, 2022
No Code AI/ML platform

NoCodeAIML No Code AI/ML platform - Community Edition Video credits: Uday Kiran Typical No Code AI/ML Platform will have features like drag and drop,

Bhagvan Kommadi 5 Jan 28, 2022
Numenta published papers code and data

Numenta research papers code and data This repository contains reproducible code for selected Numenta papers. It is currently under construction and w

Numenta 293 Jan 06, 2023
Domain Generalization with MixStyle, ICLR'21.

MixStyle This repo contains the code of our ICLR'21 paper, "Domain Generalization with MixStyle". The OpenReview link is https://openreview.net/forum?

Kaiyang 208 Dec 28, 2022