PLACE: Adaptive Layout-Semantic Fusion for Semantic Image Synthesis (CVPR 2024)

Introduction

The source code for our paper "PLACE: Adaptive Layout-Semantic Fusion for Semantic Image Synthesis" (CVPR 2024)

[Project Page] [Code] [Paper]

Overview

Quick Start

Installation

git clone 
cd PLACE
conda env create -f environment.yaml
conda activate PLACE

Data Preparation

Please follow the dataset preparation process in FreestyleNet.

Running

The pre-trained models can be downloaded from GoogleDrive and should be put into the ckpt folder.

After the dataset and pre-trained models are prepared, you may evaluate the model with the following scripts:

# evaluate on the ADE20K dataset
./run_inference_ADE20K.sh
# evaluate on the COCO-Stuff dataset
./run_inference_COCO.sh

For out-of-distribution synthesis, you just need to modify the ADE20K or COCO dictionary in the dataset.py

Citation

@article{lv2024place,
  title={PLACE: Adaptive Layout-Semantic Fusion for Semantic Image Synthesis},
  author={Lv, Zhengyao and Wei, Yuxiang and Zuo, Wangmeng and Kwan-Yee K. Wong},
  journal={IEEE Conference on Computer Vision and Pattern Recognition},
  year={2024}
}

Contact

Please send mail to cszy98@gmail.com