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

[Project Page] [Code] [Paper]

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

Please follow the dataset preparation process in FreestyleNet.

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

@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} } 

Please send mail to cszy98@gmail.com