The implementation of 'Image synthesis via semantic composition'.

Related tags

Deep LearningSCGAN
Overview

Image synthesis via semantic synthesis [Project Page]

by Yi Wang, Lu Qi, Ying-Cong Chen, Xiangyu Zhang, Jiaya Jia.

Introduction

This repository gives the implementation of our semantic image synthesis method in ICCV 2021 paper, 'Image synthesis via semantic synthesis'.

Teaser

Our framework

framework

Usage

git clone https://github.com/dvlab-research/SCGAN.git
cd SCGAN/code

To use this code, please install PyTorch 1.0 and Python 3+. Other dependencies can be installed by

pip install -r requirements.txt

Dataset Preparation

Please refer to SPADE for detailed execution.

Testing

  1. Downloading pretrained models, then putting the folder containing model weights in the folder ./checkpoints.

  2. Producing images with the pretrained models.

python test.py --gpu_ids 0,1,2,3 --dataset_mode [dataset] --config config/scgan_[dataset]_test.yml --fid --gt [gt_path] --visual_n 1

For example,

python test.py --gpu_ids 0,1,2,3 --dataset_mode celeba --config config/scgan_celeba-test.yml --fid --gt /data/datasets/celeba --visual_n 1
  1. Visual results are stored at ./results/scgan_[dataset]/ by default.

Pretrained Models (to be updated)

Dataset Download link
CelebAMask-HQ Baidu Disk (Code: face)

Training

Using train.sh to train new models. Or you can specify training options in config/[config_file].yml.

Key operators

Our proposed dynamic computation units (spatial conditional convolution and normalization) are extended from conditionally parameterized convolutions [1]. We generalize the scalar condition into a spatial one and also apply these techniques to normalization. sc-ops

Citation

If our research is useful for you, please consider citing:

@inproceedings{wang2021image,
  title={Image Synthesis via Semantic Composition},
  author={Wang, Yi and Qi, Lu and Chen, Ying-Cong and Zhang, Xiangyu and Jia, Jiaya},
  booktitle={ICCV},
  year={2021}
}

Acknowledgements

This code is built upon SPADE, Imaginaire, and PyTorch-FID.

Reference

[1] Brandon Yang, Gabriel Bender, Quoc V Le, and Jiquan Ngiam. Condconv: Conditionally parameterized convolutions for efficient inference. In NeurIPS. 2019.

Contact

Please send email to [email protected].

Owner
DV Lab
Deep Vision Lab
DV Lab
Code for "Finding Regions of Heterogeneity in Decision-Making via Expected Conditional Covariance" at NeurIPS 2021

Finding Regions of Heterogeneity in Decision-Making via Expected Conditional Covariance Justin Lim, Christina X Ji, Michael Oberst, Saul Blecker, Leor

Sontag Lab 3 Feb 03, 2022
[ACM MM2021] MGH: Metadata Guided Hypergraph Modeling for Unsupervised Person Re-identification

Introduction This project is developed based on FastReID, which is an ongoing ReID project. Projects BUC In projects/BUC, we implement AAAI 2019 paper

WuYiming 7 Apr 13, 2022
The official implementation of our CVPR 2021 paper - Hybrid Rotation Averaging: A Fast and Robust Rotation Averaging Approach

Graph Optimizer This repo contains the official implementation of our CVPR 2021 paper - Hybrid Rotation Averaging: A Fast and Robust Rotation Averagin

Chenyu 109 Dec 23, 2022
TensorFlow Implementation of Unsupervised Cross-Domain Image Generation

Domain Transfer Network (DTN) TensorFlow implementation of Unsupervised Cross-Domain Image Generation. Requirements Python 2.7 TensorFlow 0.12 Pickle

Yunjey Choi 865 Nov 17, 2022
PyTorch implementation for the ICLR 2020 paper "Understanding the Limitations of Variational Mutual Information Estimators"

Smoothed Mutual Information ``Lower Bound'' Estimator PyTorch implementation for the ICLR 2020 paper Understanding the Limitations of Variational Mutu

50 Nov 09, 2022
Progressive Growing of GANs for Improved Quality, Stability, and Variation

Progressive Growing of GANs for Improved Quality, Stability, and Variation — Official TensorFlow implementation of the ICLR 2018 paper Tero Karras (NV

Tero Karras 5.9k Jan 05, 2023
Generate Contextual Directory Wordlist For Target Org

PathPermutor Generate Contextual Directory Wordlist For Target Org This script generates contextual wordlist for any target org based on the set of UR

8 Jun 23, 2021
Code release for Hu et al. Segmentation from Natural Language Expressions. in ECCV, 2016

Segmentation from Natural Language Expressions This repository contains the code for the following paper: R. Hu, M. Rohrbach, T. Darrell, Segmentation

Ronghang Hu 88 May 24, 2022
PointCNN: Convolution On X-Transformed Points (NeurIPS 2018)

PointCNN: Convolution On X-Transformed Points Created by Yangyan Li, Rui Bu, Mingchao Sun, Wei Wu, Xinhan Di, and Baoquan Chen. Introduction PointCNN

Yangyan Li 1.3k Dec 21, 2022
A python package to perform same transformation to coco-annotation as performed on the image.

coco-transform-util A python package to perform same transformation to coco-annotation as performed on the image. Installation Way 1 $ git clone https

1 Jan 14, 2022
Doubly Robust Off-Policy Evaluation for Ranking Policies under the Cascade Behavior Model

Doubly Robust Off-Policy Evaluation for Ranking Policies under the Cascade Behavior Model About This repository contains the code to replicate the syn

Haruka Kiyohara 12 Dec 07, 2022
Official PyTorch Implementation of Hypercorrelation Squeeze for Few-Shot Segmentation, arXiv 2021

Hypercorrelation Squeeze for Few-Shot Segmentation This is the implementation of the paper "Hypercorrelation Squeeze for Few-Shot Segmentation" by Juh

Juhong Min 165 Dec 28, 2022
Pynomial - a lightweight python library for implementing the many confidence intervals for the risk parameter of a binomial model

Pynomial - a lightweight python library for implementing the many confidence intervals for the risk parameter of a binomial model

Demetri Pananos 9 Oct 04, 2022
TaCL: Improving BERT Pre-training with Token-aware Contrastive Learning

TaCL: Improving BERT Pre-training with Token-aware Contrastive Learning Authors: Yixuan Su, Fangyu Liu, Zaiqiao Meng, Lei Shu, Ehsan Shareghi, and Nig

Yixuan Su 79 Nov 04, 2022
PyTorch implementation of MulMON

MulMON This repository contains a PyTorch implementation of the paper: Learning Object-Centric Representations of Multi-object Scenes from Multiple Vi

NanboLi 16 Nov 03, 2022
Official implementation of "SinIR: Efficient General Image Manipulation with Single Image Reconstruction" (ICML 2021)

SinIR (Official Implementation) Requirements To install requirements: pip install -r requirements.txt We used Python 3.7.4 and f-strings which are in

47 Oct 11, 2022
这是一个unet-pytorch的源码,可以训练自己的模型

Unet:U-Net: Convolutional Networks for Biomedical Image Segmentation目标检测模型在Pytorch当中的实现 目录 性能情况 Performance 所需环境 Environment 注意事项 Attention 文件下载 Downl

Bubbliiiing 567 Jan 05, 2023
This repository contains the database and code used in the paper Embedding Arithmetic for Text-driven Image Transformation

This repository contains the database and code used in the paper Embedding Arithmetic for Text-driven Image Transformation (Guillaume Couairon, Holger

Meta Research 31 Oct 17, 2022
DI-HPC is an acceleration operator component for general algorithm modules in reinforcement learning algorithms

DI-HPC: Decision Intelligence - High Performance Computation DI-HPC is an acceleration operator component for general algorithm modules in reinforceme

OpenDILab 185 Dec 29, 2022
Generates all variables from your .tf files into a variables.tf file.

tfvg Generates all variables from your .tf files into a variables.tf file. It searches for every var.variable_name in your .tf files and generates a v

1 Dec 01, 2022