Since Danne's suggestion that I should use separate card readers for MLVFS using card spanning, I've been doing every video in at least 3000 pixels across, and having zero problems!
Lately I have gotten lazy (and impatient) so I have switched from "superscaling" in resolve (GPU intensive and slower, but with beautiful results) to simple upscaling using the SINC algorithm. The issue with sinc is how it strongly emphasizes any aliasing in the source footage (very badly, actually to the point of unusability). But it seems that this only happens when the source footage is below a certain resolution, for I have never seen it at all in these latest videos.
This video was shot at 3072*1536 (I really like 2:1 aspect ratio) and upscaled to 4k using simple SINC. To me it looks like it was shot at 4k.
speaking of 4k, make sure to view it at 4k to avoid youtube quality degradation...
https://youtu.be/vNrEmilbvdw
I can't praise MLVFS highly enough. To pull the cards from the camera and have a completed edited graded video uploading minutes later is pretty amazing!
PS: the banner image for the video is a frame from the video, cropped 200%
that's great!
you need to try Topaz Video AI using the Gaia engine, the 4K upscale is just insane, slower than Resolve's superscaling but with best results.
Hopefully we will get faster options soon!
Well Its sure, the GPU market is all on AI computing they are so much ressources put on (Upscaling / DLSS / FSR / 3D modeling from any camera etc) that we could be sure that it gonna evolve and be faster/better, Its already real time with AMD CPU and NVIDIA GPU, also the upscaling code of AMD FSR 2.0 is open source now
-> https://gpuopen.com/fidelityfx-superresolution-2/
Haven't heard about MLVFS Im gonna check that :), IMCE showed that using a diffusion filter can help a bit with Aliasing (with the EOS M at least).
Hi, the SINC upscale => Can you explain how to do ? Please