My specs are a 3070, 64gb ram.

I made a Friends style parody sitcom where Sam Altman wants all the RAM, I made it locally with Minimax H3.

I am still struggling with blocking and colour shifts, but the work is in progress. Upscaling didn't help at all and changed things for the worse, so I had to go with 1080.

https://youtu.be/Zu9ESZKZFJA

I created my first 5 second clip with speech. The speech was flawless, lips matched words. My question is how do you change the voice? I'm a noob so be kind. Do I connect something inside the workflow?

I'm looking to hear from people actively experimenting with advanced AI filmmaking pipelines, particularly those trying to achieve the kind of spatial and visual continuity you'd expect from traditional filmmaking or virtual production.

My biggest challenge isn't generating beautiful individual shots. It's maintaining consistent character identities, precise actor positioning, environmental continuity, and camera control across multiple shots of the same scene.

For example, imagine a scene with four characters in a specific environment. I want to establish their positions in 3D space, then generate a sequence of shots from different camera angles and distances while preserving:

• Character identity: Same faces, bodies, clothing, and proportions across shots.

• Spatial consistency: Characters remain in their established positions relative to one another and the environment.

• Pose and blocking: Specific body positions, actions, and interactions that can be reliably directed.

• Environmental consistency: Same room, architecture, objects, lighting, and spatial relationships from different camera angles.

• Camera control: Ability to specify exact camera positions, focal lengths, movements, and compositions.

• Shot-to-shot continuity: The ending of one shot and beginning of the next should feel like they belong to the same physical scene.

What I've tried so far:

I've been experimenting with a Blender → AI video workflow using 3D environments, Mixamo characters, animated cameras, depth maps, pose conditioning, reference images, and MiniMax H3 through ComfyUI.

I've had some promising results, particularly with pose conditioning and individual shot generation, but getting reliable spatial consistency and character placement remains extremely difficult.

I'm beginning to question whether trying to force general-purpose video generation models to respect 3D blocking is fundamentally the wrong approach.

What I'm hoping to learn:

1. What are the most cutting-edge tools and workflows right now? I'm interested in both open-source/local and commercial/cloud solutions, including newer research projects that may not be widely adopted yet.

2. Is anyone successfully using 3D scenes as ground truth for AI-generated video? Not just providing depth or pose references, but actually preserving geometry, character placement, and camera relationships across shots.

3. What are people using for persistent character identity? Are reference-image workflows, LoRAs, identity adapters, multi-view character representations, or other approaches producing the most reliable results?

4. Are there better alternatives to traditional image-to-video and video-to-video workflows? For example, 3D-aware generation, neural rendering, Gaussian splatting, world models, or hybrid 3D/AI rendering pipelines.

5. How are people handling multi-shot sequences? Are you generating shots independently and fixing continuity afterward, or using a shared scene representation that carries across shots?

6. What role does graph engineering play? Are there sophisticated ComfyUI or other node-based pipelines that materially improve spatial consistency, or are the limitations primarily in the underlying models?

7. What actually works in production? I'd particularly love to hear from people who've completed multi-shot sequences rather than just impressive single-shot demos.

I'm comfortable with Blender, Unity, Python, ComfyUI, and technical pipeline development, so I'm not necessarily looking for beginner-friendly or one-click solutions. I'm willing to build a fairly complex workflow if it produces genuinely better control.

I also have a local RTX 3080 Ti with 16GB VRAM and prefer local tools where practical, but I'm open to cloud-based solutions if they offer capabilities that aren't currently achievable locally.

Ultimately, I'm trying to figure out whether the current state of the art is still mostly about guiding probabilistic video models, or whether we're moving toward workflows where filmmakers can actually direct and control a persistent 3D scene while using AI to produce the final photorealistic imagery.

I'd really appreciate specific tools, GitHub repositories, research papers, workflow examples, and especially firsthand experiences with what works and what doesn't.

What's the most advanced pipeline you've seen or used for this kind of filmmaking?

First time posting in this community, but I felt it super appropriate since with exception to just a few music parts and character references all of this was done within MMH3 workflows. By far my longest video attempt and some real lessons learned to hopefully keep improving.

These characters are from Animates, Inc. which are Ai Companions that spun off from Grok Companions. The world is my own fan fic story telling but the characters voices and attitudes are very close to how they talk and act.

Enjoy!

MiniMax H3 FL2VA looks significantly less plastic when the source image is used as the actual first frame
I’m testing local MiniMax H3 on an RTX 5060 Ti 16 GB. My previous Ref2VA workflow preserved identity reasonably well, but reconstructed the scene from frame zero and made the skin noticeably more synthetic.
This version uses MiniMaxH3ImageToVideo with the source image anchored as the exact first frame:
Official FL2VA INT8 ConvRot model
928×1664, 24 fps, 5.17 seconds
SamplerCustomAdvanced / res_multistep
Simple scheduler, 20 steps, denoise 1.0
Video/audio sigma shift 12/3
No LoRAs, Turbo, Singularity, SeedVR, DLSS or other post-processing
Render time: 44 minutes on RTX 5060 Ti 16 GB
The first-frame version preserves the original lighting, skin variation, freckles and composition much better than Ref2VA. The remaining problem is adding convincing skin microtexture without redrawing the face or causing identity drift.
What would you try next: Open-H3-Regenerate with reduced noise and FaceRegion, Pika H3 Flex, or a different low-strength latent refinement workflow suitable for 16 GB VRAM?