Nice find! I hand't seen this before (and will take a deeper look later). It looks like this is an approach to better utilize the GPU memory. And, we would probably benefit from this to get more of a speed-up, which would also help us get better video quality.

I do not think they are running in real time though. From the website: "Personal RTX 4090 generates at speed 2.5 seconds/frame (unoptimized) or 1.5 seconds/frame (teacache)." That means it would take them 37.5s to generate 1 second of video, which is fast for video but way slower than real time.

Yep, this is way slower but considered SOTA on video-gen open source.

I mostly meant the using the previous frames to generate new frames insight that reminded me but lack knowledge on the specifics of the work

glad if its useful for your work/research to check out the paper

edit: the real-time-ness of it also has to have into equation what HW are you running your model on, obviously easier to make so on a H100 than a 3090, but these memory optimizations really help to make these models usable at all for local stuff, which is a great win i think for overall adoption/further stuff being build upon them a bit like sd-webui from automatic1111 alongside stable diffusion weights models being open sourced was a boom on image gen a couple years back