Hi, Em qua., 4 de mar. de 2020 às 09:57, YATENDRA SINGH <yatend...@iitbhilai.ac.in> escreveu: > > Thank you for explaining the procedure. > I have posted my own project proposal on the page you had instructed me to. > Looking forward to the feedback.
Have you contacted any possible mentor? If not, I would suggest you to make your project idea less generic. For example: which dnn models are you planning to use (both for the qualification and the project)? Are they already supported by our dnn infrastructure? our dnn module has two backends: native, which is cpu only and tensorflow. Which one are you going to support? or both? > > > Regards, > Yatendra Singh. > > On Tue, Mar 3, 2020 at 10:19 PM Pedro Arthur <bygran...@gmail.com> wrote: > > > Hi > > > > Em ter., 3 de mar. de 2020 às 09:24, YATENDRA SINGH > > <yatend...@iitbhilai.ac.in> escreveu: > > > > > > Hi, > > > I am a third year CSE student at the Indian Institute of Technology > > Bhilai, > > > and would like to contribute to ffmpeg this year. I have > > > relevant experience with Machine Learning and would like to work on > > > improving the video frame interpolation already implemented. With such a > > > plethora of great Machine Learning Algorithms being published every year > > at > > > prestigious conferences I would aim to read the relevant academic papers > > > and implement the best suited technique for the task. For example, Depth > > > Aware Video Frame Interpolation (DAIN CVPR-2019) is supposedly the state > > of > > > the art method on Vimeo90k and MiddleBury > > > <https://paperswithcode.com/task/video-frame-interpolation> but at the > > same > > > time Frame Interpolation with Generative Adversarial Network(FIGAN), uses > > > not CNN but multi-scale synthesis( MS ) to get higher speeds. > > > Looking forward to hearing from you soon. > > > > > > Yatendra SIngh > > > Frame Interpolation with Multi-Scale Deep Loss Functions and Generative > > > Adversarial NetworksFrame Interpolation with Multi-Scale Deep Loss > > > Functions and Generative Adversarial NetworksFrame Interpolation with > > > Multi-Scale Deep Loss Functions and Generative Adversarial Networks > > > > I suppose this project is your own idea as it is not listed in the > > projects page, right? > > > > I think it would be good to add you idea under "Your Own Project Idea" > > section in [1] adding as much information as possible so that we can > > evaluate your idea and possible assign a mentor / backup mentor. > > A few things I think are important to evaluate your project are: > > *have a well defined "expected result", will it be a filter? or > > something else? we already have a dnn module and a dnn_processing > > filter, will your project be using it? > > > > *what is the amount of work that will be done during the project, more > > or less this is related to above "expected result" > > > > *define a qualification task, we can discuss it after the above is define > > > > *sell your idea (not strictly necessary but may help evaluating your > > project), why is it useful feature to have, what improvements it > > brings, etc > > > > [1] - > > https://trac.ffmpeg.org/wiki/SponsoringPrograms/GSoC/2020#YourOwnProjectIdea > > _______________________________________________ > > ffmpeg-devel mailing list > > ffmpeg-devel@ffmpeg.org > > https://ffmpeg.org/mailman/listinfo/ffmpeg-devel > > > > To unsubscribe, visit link above, or email > > ffmpeg-devel-requ...@ffmpeg.org with subject "unsubscribe". > _______________________________________________ > ffmpeg-devel mailing list > ffmpeg-devel@ffmpeg.org > https://ffmpeg.org/mailman/listinfo/ffmpeg-devel > > To unsubscribe, visit link above, or email > ffmpeg-devel-requ...@ffmpeg.org with subject "unsubscribe". _______________________________________________ ffmpeg-devel mailing list ffmpeg-devel@ffmpeg.org https://ffmpeg.org/mailman/listinfo/ffmpeg-devel To unsubscribe, visit link above, or email ffmpeg-devel-requ...@ffmpeg.org with subject "unsubscribe".
