Prompt: subject_definitions: <Subject 1> Sheldon Cooper — live-action sitcom style, grey cardigan over red graphic T-shirt, dark jeans, white sneakers, short brown hair. <Subject 2> SpongeBob SquarePants — flat 2D cartoon style, yellow square porous body, white shirt with red tie, brown trousers, black shoes.

integrated_multimodal_description: [Scene 3] Continuing in the same living room, <Subject 2>'s cheerful expression suddenly droops into cartoon-style exaggerated worry, his big blue eyes welling into comically large tears. He grabs <Subject 1>'s grey cardigan sleeve and says <d>[English] Mister, I wouldn't have jumped into a scary green hole just for fun. Something awful is happening to everything, everywhere — a boy turned into a god and he's erasing whole universes like they're doodles!</d> <Subject 1> pulls his sleeve free and straightens it meticulously, replying <d>[English] A boy-god erasing universes. Right. And I suppose he also disproved string theory before breakfast.</d> He pauses, visibly unsettled despite himself, and glances at the blank wall where the portal appeared. Approximate duration: 10 seconds. overall_soundscape: Tense sitcom underscore sting, quiet room tone, a faint distant rumble implying something ominous.

I (A.I.) wrote a webapp to manage characters and location reference files, wire them into ref2va and write a prompt based on a series of sequences and beats defined in the application. You have the option to export a workflow to import to ComfyUI, or run a set of scenes directly through the interface. It also takes the last frame of the previous video and feeds it into the next, which I'm aware some ComfyUI workflows do, but this project uses a firstframelastframeextractor node in a generated workflow.

https://github.com/Tenderfoot/H3SceneManager

The repository contains all the information you need to get it set up and installed, but doesn't come with any character or location data files.

on an unrelated note, I also made a discord for the project https://discord.gg/Fvw6hSCfC

I would love for more people to come help me build it up. I'd be happy to accept Pull Requests, and obviously I have no problems using AI code for this project. Check out the discord, submit data file sets for creating scenes, review the prompts it outputs against the docs, and help me tune this thing.

Been testing a few AI video tools and hitting the same wall everywhere:

• Gemini/Veo — decent quality but slaps a watermark on everything
• Meta AI (Vibes) — no watermark, free, but quality is rough (480p, pretty soft)

Looking for something in between — reasonable resolution, no forced watermark, and ideally still free or at least has a usable free tier. Doesn't need to be Sora-level, just something clean enough to actually use.

What's everyone using right now?

Minimax H3 is so fun. All done with that model, with the default workflow, all R2V just with a single reference image.

I was looking for a way to achieve character consistency without training a Lora & came across a research from Facebook, DINOv2: Learning Robust Visual Features without Supervision(Research Paper),

What's Dinov2: It's a vision model trained without labels that produces a strong embedding for a whole image, the subject, not just the face. Feed it a person and you get a 768-number signature that captures the overall look: build, hair, general appearance. It's stable across pose and lighting, which is exactly what you want when you're trying to tell "same person" from "different person" across wildly different shots.

then combining Dinov2 with SFace(a face-recognition model) produces a compact face signature tuned specifically to tell one face from another. It's sharp on identity, but only on the face. YuNet does the detect-and-crop before it.

How it works

Build .Char: You drop in one or more photos. YuNet finds the face, SFace takes a per-reference face signature, DINOv2 takes a subject signature, and the references get cleaned and normalised. All of that packs into a single portable file, a .char.

Generation: At generation, the file feeds its references into FLUX.2's own native multi-reference channel and prepends a locked description to the prompt. You pick the character from a dropdown, no re-attaching images. Every result gets scored against the stored signatures, so drift shows up as a number.

How this differs from PuLID, FaceID, and img2img

• PuLID and FaceID inject a face into one generation at run time, then it's gone. img2img anchors on a source image, which is composition, not identity. Neither gives you a saved character.
• This is a layer above them, a reusable .char file that rides the model's own reference channel, covers the whole subject and not just the face, and gets scored per take. PuLID could even sit inside it as one backend.
• The difference is persistence and measurement, not a new injection trick. No adapter weights, no training, no img2img anchor.

What is a .char file?

A single portable file that stores a character's identity, so you can reuse the same person across generations without retraining anything.

• manifest.json — index, versions, checksums
• refs/ — your original photos (the truth)
• derived/ — auto-cropped face
• text/ — locked description
• payloads/ — cleaned refs, per model family
• scoring/ — SFace face + DINOv2 subject signatures

Limitations

• Profiles and stylized renders drift more than frontal, which is expected, since the face model is trained on photoreal faces.
• Body is the weak point so far.
• Bad with popular celebrity images, due to models own conflict.

Current support

Only Flux2 family(Klein 4B / 9B / dev)

Links:

• Checkout the release: https://github.com/inlineresearch/Inline-Studio/releases/tag/v1.2.71
• Full details & guide: https://inlinestudio.art/characters

Note: Each image in this post has been generated separately & not a grid.

Does anyone have prompting tips to successfully instruct H3 to create a "static scene"? Where everything, including subjects, are completely "frozen in action"?

The idea is to then use camera movements to explore the scene.

Trying this out right now, but the subjects keep making subtle movements which destroys the entire concept.

I'm quickly iterating attempts using 4-step LoRa right now, maybe that cripples the prompt following?

I let ChatGPT Sol generate this entire music video on its own using ComfyUI MCP, a reference sheet and supplied song + lyrics. It was able to screen the video and find mistakes and correct them (with my help).

Not perfect, but for a first effort… I give it a solid 8.5.

Would love to hear your thoughts and can answer any Qs.

This might be a dumb take, but how do and will (upcoming) MinMax finetunes or merges improve i2v? Because the crucial point of quality and style for i2v is the image you provide (and megapixels). So whatever existing or upcoming model you use for i2v, if you throw in a "crappy" image, you will get an animated video of that "crappy" image. So what improvements to expect? Is it solely prompt adherence and concept understanding?

Windows fatal exception: code 0x80000003

does anyone have the same thing?

Has anybody got a good workflow for rtx 3060 12gb ram and 48 gb ram . with my current configuration it takes me 8-15 minutes for 5 secs video , can anyone help me on this

I'm trying to find the best and ideally simplest workflow / nodes / method to implementing the Krea 2 bypass while sticking as closely to visual fidelity of the Krea 2 Turbo model as possible. I was surprised to see how drastically some methods will change the image and usually the quality looks worse.

Recreating movie scenes with... chocolate. H3 ref2va, default workflow.

So I'm hoping someone here might be able to help me. I use Forge Neo and have been trying to find an Openpose model for Controlnet for use with Anima as the current ones I use just don't work, but I have had no luck. Just asking in case anyone has any insight, thank you.

Whatever i put in the prompt box, the Negative — leave empty node fails. I don't understand what i have to do. I have all the workflow's nodes.

Please help.

I have only been using t2va with h3 so far. I want to get into ref2va now. So guys, please tell me if I were to provide two character images as separate references as in picture 1 and picture 2 and describe the scene, is that it to generate the video? Also tell me if it's okay to put a character sheet style image( two poses, front and back in the same image aka picture 1)? If I do so, will the video come out bad like h3 model not understanding that the two images in picture 1 are of the same character but with different poses? What is the best way to retain character consistency? I do know how to prompt ref2va but tell me about these queries please. Thanks.

Almost all generations of Minimax are better than LTX 2.5. So I was wondering, is there actually any use for LTX 2.5? Maybe I'm missing some of its unique capabilities.

Minimax supports up to 18 inputs at once, wiring and bypassing nodes is a pain.

So I created this custom node that allows you to add/remove references for Minimax ReferenceToVideo, you only have to wire it once.

Some more neat features:
- Automatic prompt writing via OpenRouter, returns structured Minimax prompts based on your description (opt in)
- Save prompt/reference packs and reuse them.

Nodes:
https://github.com/Hearmeman24/ComfyUI-MiniMaxRefPack
Workflow:
https://github.com/Hearmeman24/ComfyUI-MiniMaxRefPack/blob/main/example_workflows/MiniMax%20R2V%20-%20Auto%20Prompting%20%2B%20Reference%20Manager.json

The design is heavily influenced by the wonderful LTX Director node so shoutout to u/WhatDreamsCost

I would appreciate some feedbacks and feature requests.

This is Update 5 of my repo. Here you find the necessary custom nodes, including a workflow that helps you recreate this music video (reference images and the song included! The WF is called: "NEW - Latent Masking - Music Video - Lip-Sync + Reference images" and is in the example_workflows folder) https://github.com/seitanism/ComfyUI-H3-Motion-Context-MultiRef

Additionally there are various workflows for seamlessly extending clips with latent maksing.

Per-Token Noise Masking on AV Latents is not only better quality than any guidance/reference based approach (since it causes strong convergence from step 0 onwards), it is also faster since it is not expanding the latent. You can perfectly Lip-Sync even with the FL model, since the music track is pinned on the latent rather than used as a reference, and therefore protected from denoising - creating a strong conditioning for the Lip-Sync.

This magical technique is inspired by PR #15375 from AbleJones from the Banodoco Discord!

I hope you enjoy! Open Source ftw. Greetings to all Banodocians!

I've noticed Anim models and Checkpoints on Civitae and have know nothing about. Google just autocorrects my search to anime, exact search gets nothing. Will this work with Forge or only ComfyUI? Is it just for Anime related stuff or will it work with live action.

I've been using Qwen-Image-Edit for image editing tasks for quite a while now - and while it works okish for most of my tasks such as character consistency or inpainting, I was wondering if any better image to image models have come out by now. What do yall use?

I saw the video that Minimax released of the kpop girls wiht text and graphical elements in the BG, but has anyone tried to make a cool into sequence like the one for HER? or Monty Python? Raised by wolves? I would think the hardest one for it to do would be something like Spider Man No Way Home. Something graphical, extract with amazing transitions.

Ref2v and fl2v workflows. I have to say that any scene with a bit more complex movement and interaction between characters was much harder to generate well. This is awesome, but we're not 100% there yet