Deep Image Harmonization

Project webpage: https://sites.google.com/site/yihsuantsai/research/cvpr17-harmonization <br /> Contact: Yi-Hsuan Tsai (wasidennis at gmail dot com)

Paper

Deep Image Harmonization <br /> Yi-Hsuan Tsai, Xiaohui Shen, Zhe Lin, Kalyan Sunkavalli, Xin Lu and Ming-Hsuan Yang <br /> IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.

This is the authors' demo code described in the above paper. Please cite our paper if you find it useful for your research.

• One re-implementation of our dataset and model: https://github.com/bcmi/Image_Harmonization_Datasets

Installation and Usage

• Download and unzip the code.

• Install Caffe: http://caffe.berkeleyvision.org/.

• Download the pre-trained caffe model and move it under the model folder.

• Run demo.py on real composite images (including our test set collected in the paper).

Evaluation Set

• Download our complete set of real composite images, including our harmonization results here.

Note

The model, code and dataset are available for non-commercial research purposes only.

Log

• 03/2017: demo code released
• 05/2017: complete evaluation set released