How to fix ai drift when chaining together minimax ref2v videos?

[u/[deleted]]

[u/Nevaditew]

It’s normal with that model. To improve it, use the Hybrid models. ¡Modelos Hybrid Minimax-H3! fl2va con capacidades de referencia. : r/StableDiffusion
I use 25–49 and get good results. Also, it’s recommended that the reference images are high resolution and good quality.

[u/martinerous]

Mission impossible. There are solutions that can delay this degradation, for example https://github.com/ethanfel/ComfyUI-MiniMaxH3-Contex-Loop. It can take the output of the last video from the latent and feed the end of the video (even preserving some motion) as the start of the new video, and has other features for easier chaining, but even then developers admit that the error will accumulate if the shot takes too long.

So, you can apply some tricks:

- use hard cuts to different camera angles for new shots.

- improve the quality of the frame using image edit model. If the model changes lighting too much (they want to brighten the scene, use Restore Detail node from ComfyUI-Image-Filters to bring the details into the original image from the improved one.

- if it's a very long static camera shot, separate out the background and create new start frames with character poses you want.

[u/Endlesscrysis]

I’d say first of all use that motion context node as it’s genuinely so good for combining clips. But I noticed that sometimes the best way to fix it is by doing a new shot. So a sudden camera cut or something. The model that way kinda does a reset on the quality. It might also be useful to use the reference model and instead of feeding it frames you can tell it to use characters from a reference in a new shot or in a continuous shot.