This project is part of the course Deep Learning - MSc Data Science for Business - HEC Paris and Ecole Polytechnique
Design a mobile application prototype that allows users to do fine-grained image editing in real-time before uploading the social applications on their mobile phones.
We adapted the semantic segmentation technique (RefineNet) to identify the human part in images. Then we use the neural style transfer to transfer the part of image that user selected. For more details, please see the slides.
We finetuned and pruned the RefineNet to our use case.
Our smallest model: LightNet-MobileNet acheived 0.809 mIoU with only 13MB size, which outperforms the off-the-shelf DeepLabV3 (0.806 mIoU, 233MB) in this specific task in terms of the quality, size and inference speed.
This project was conducted between 2019-Nov-05 and 2019-Nov-11.
The RefineNet model architecture is adapted from https://github.com/ansleliu/LightNet