This week, our team met up with Joel and Byron, and we discussed our progress on the project. We went into detail about the specific use of VMAF in the training part of the CNN, and we discussed various problems/issues that may arise with the use of VMAF, and came up with several solutions. Byron reiterated the importance of traditional DSP methods, specifically, wanting us to justify and confirm how using a CNN would be superior to those traditional methods, and I incorporated that into our design presentation.
Since we didn’t receive AWS credits until much later in the week, I downloaded our intended dataset and attempted to benchmark VMAF as well as Anime4K locally, a project on Github with similarities to our project, to see how they would perform. Since there were many different videos available on the website where I was getting my dataset (CDVL), I ran into a slight issue with the difference between 1080i and 1080p, as well as the FPS of videos in the dataset, but after discussing with James, I managed to compile a list of videos which were 1080p @30FPS, and worked with my team members to successfully benchmark VMAF and Anime4K. Our development of Python code for training was delayed, since we couldn’t start until much later on in the week, and we intend to catch up on that ASAP as soon as our design presentation is concluded.
I also met up with TAs Joel and Edward outside of class hours to further discuss our project and refine the details in preparation for our presentation. I also wrote the team status report for this week, and worked on the design presentation with my team members.