Wan - 2.1 I2V SVI Film - 10 windows (testing workflow).json
Wan - 2.1 I2V SVI Film - 5 window loop (unofficial).json
Wan - 2.1 I2V SVI One Shot - 10 windows (testing workflow).json
Wan - 2.1 I2V SVI One Shot - 5 window loop (unofficial).json
Shot is for static scenes, most stable, especially with a prompt / lora for a specific action.
Film is for dynamic scenes / multiple prompts over the course of more than 5 seconds. OPT is a version tuned more on human preferences.
Film Transition is for scenes with major changes between shots.
Made by epfl lab. These loras allow the extension of wan's generations up to a unlimited amount of frames while still following the given prompt / prompts throughout.
https://github.com/vita-epfl/Stable-Video-Infinity
Description
FAQ
Comments (19)
Why workflow on a different site? Can you upload WF on a Civitai?
What is the workflow to use for this? The one in the description seems to be a Wan 2.2 workflow, with no mention to SVI
It was the WF for the swimming animation but I put up some more straightforward ones
Ok, but to give some context please also put the link to the source thread, since they are testing wf and very likely to be modified soon :
https://github.com/kijai/ComfyUI-WanVideoWrapper/issues/1519#issuecomment-3447933556
@nekotxt got good results with it already, will update if they change
I have been able to adapt this workflow to be used with Wan 2.2, but since I am using GGUFs (cannot run the FP8s I don't have enough VRAM) I have a problem with the Lora combine (GGUFs do not support the function apparently) - Would you suggest any workaround?
Also, is there any easy way to adapt this workflow to use different LORAs per part of the video?
Thanks!
get the GGUF creator from that City96 guy and convert them to GGUF yourself but I'm about to look at this as this was my exact idea and already have it built I just need Co-pilot to create a node that automates it for me as these nodes rarely have what I am trying to accomplish so one must get savvy with python if you ever want to break from the weirdness.
Any plans to make a 2.2 version? Or is there a way to make this work with 2.2 already?
I have 10 SVI LoRAs. Two of them are 2.1, the rest are 2.2. Search for SVI PRO.
I find it a little odd the people who already need to use quants to run models now want to generate 300 frames at once... That said, you can load an existing video, grab a batch of at least 16 frames from the end of it and encode that. Use it as your prev_latent in the SVI node. For the anchor, put a 'save latent' node after initial latent that comes out of your main encoder- use 'load latent' to call this file for your extension. This will enable you to run an independent generation using samples from a previous one. It works. Really, really well.
This sounds like it would work. Do you have a workflow you can share?
@evert_guy I have a FLF workflow that uses SVI posted on my models page, specifically for capping off long generations using this method. Go to my models page and download that and take a look at how I set up the first input to grab end frames and send them to an encoder. You easily adapt this to encode, say, 81 frames from the end and send it to SVI node as your previous latent. Don't do what I said above with the anchor. Instead, send the LAST frame of the video to the encoder that sets your I2V input image- that's your new anchor (NOT the previous generation's starting image latent- that will make the video start back at the beginning) The SVI encoder combines the anchor (incoming image) and prev (incoming motion) into one embed, because you can only have one embed, of course. You can also pull both inputs from the same encoder - depends on how your setup is configured already, whatever is easier. This stuff gave me fits at first, but I've got it down I think. One thing you should definitely do: put a save latent node onto all of your workflows and make a folder for them. That way anything you want to extend in the future, you don't have to worry about re-encoding. I'll be posting my own 4-stage SVI workflow that does this, I'm still finishing the automated prompt/LoRA switching, which is a monster, stupidly way too big. But I will post it. I think instead of incorporating the above into it, I'll make a little WF specifically for making input latents to use in the main one.
Hope this made sense. If it didn't, I promise you it does work, and you can make it work despite my babbling. I believe in you soooooo much. Like, a lot.
@Ponder_Stibbons Thanks so much for the reply, I'll look through the workflow and see if I can make it work.
Hmm, i can't understand those SVI loras, can someone explain me what impact do they have on the video? pls
it worked for me but now it tell's me: 'WanVideoModel' object has no attribute 'diffusion_model'
Thank you for the workflow. However, the images are getting worse and worse with each group. At first, you can still see the cat's fur. By group number 4 or 5, the cat looks more like a plastic cat. Is there a solution that allows the images to retain their initial quality?
Sounds like what happens when you just use the last frame image to generate the next video. Thought SVI was suppose to avoid that.
@Plasmadose That also happens, at least for me, when I use this workflow. I will test other workflows with SVI models in the future. But thanks for your answer.
Details
Files
svi-film-opt-10212025_lora_rank_128_fp16.safetensors
Mirrors
svi-film-opt-10212025_lora_rank_128_fp16.safetensors
svi-film-opt-10212025_lora_rank_128_fp16.safetensors
svi-film-opt-10212025_lora_rank_128_fp16.safetensors
svi-film-opt-10212025_lora_rank_128_fp16.safetensors
svi-film-opt-10212025_lora_rank_128_fp16.safetensors
svi-film-opt-10212025_lora_rank_128_fp16.safetensors
svi-film-opt-10212025_lora_rank_128_fp16.safetensors
svi-film-opt-10212025_lora_rank_128_fp16.safetensors
svi-film-opt-10212025_lora_rank_128_fp16.safetensors
svi-film-opt-10212025_lora_rank_128_fp16.safetensors
svi-film-opt-10212025_lora_rank_128_fp16.safetensors
svi-film-opt-10212025_lora_rank_128_fp16.safetensors
Available On (1 platform)
Same model published on other platforms. May have additional downloads or version variants.
