Introduction

This page shows the results from the student projects that were part of GSoC 2019.

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Projects

OpenCL Deshake Filter

A blog post discussing this project can be found at ​https://cldfire.dev/blog/gsoc-2019/

Derain Filter

Description: This project is aimed to remove rain/haze in images/videos. It can be used for image and video processing to make them clearer and it can be a preprocessing method for many computer vision systems.This project goal was to implement deep-learning-based derain filter and dehaze filter.

Results: Contributions of the GSoC period include:

• Support of multiple DNN operations in FFmpeg, such as various padding methods (​ commit), different kinds of activation functions (​ commit) and the support of dilated convolution (​ commit). These operations are needed for the implementation of derain filter and are also common operations for neural networks.
• Implementation of ​ RSECAN model for derain filter (​ commit.
• Implementation of dehaze filter (​ commit.
• Improvements and fixes of derain and dehaze filter. Commits: ​ 1, ​ 2, ​ 3.
• Scripts for model training, evaluation and generation for derain and dehaze filter are provided in the ​ repository.

Future work: Evaluate more models for derain and dehaze. If their performance is better, they will be added to the derain filter in FFmpeg.

Mentor: Steven Liu (lq AT chinaffmpeg DOT org)

Student: Xuewei Meng (xwmeng96 AT gmail DOT com)