u/IM3D-Studios

I've been experimenting with something a little different for character consistency: using structured 3D pose data as part of the dataset-generation process for LoRA training.

Instead of generating a bunch of random images and hoping the dataset covers enough variation, I've been using controlled MetaHuman facial expressions and hand poses to deliberately build variations around the same character.

The interesting part is that the 3D poses give me something I can control and reproduce:

• specific facial expressions
• specific hand positions
• repeatable poses
• combinations of face + hand poses
• consistent character geometry

I then use those references in my ComfyUI workflows to generate the 2D training images.

The goal isn't to train the LoRA to reproduce the MetaHuman itself. It's to use the controlled pose references to create a more deliberate dataset where identity stays consistent while expression and pose change.

This seems particularly useful for characters that need to remain recognizable across a large number of generated shots.

I've been using my own MetaHuman Face Pose Library and MetaHuman Hand Pose Library for this workflow.

I'm curious if anyone else has experimented with 3D pose libraries as a structured way of generating LoRA training datasets.

It seems like there could be an interesting middle ground between manually creating every training image and completely random dataset generation.

What are you guys using for pose/expression variation when building character LoRAs?

Hi everyone, I’ve been working on a cinema-specific motion library to fill the gap in high-quality talking and emotional states for MetaHumans.

Instead of keyframing dialogue from scratch, I've utilized a professional Xsens mocap setup to capture raw performance data. This pack covers:

• Talking & Explaining: Natural lip-sync ready gestures.
• Emotional States: Genuine reaction movements (not just looped idle).
• Deliveries & Listening: Reactive motion for cinematic pacing.

Everything is 60 FPS and optimized for UE5 MetaHuman rigging to avoid the "floating" look you sometimes get with lower-quality imports.

It's available on Fab if anyone needs a reference or wants to pick it up for their pipeline. Open to any feedback on the motion blending!

I’ve been planning this upgrade for a while, but I finally pulled the trigger on the new Nvidia RTX PRO 6000 Blackwell Edition. The price tag is absolutely insane ($14k), but for my specific workflow involving heavy local LLM development and Unreal Engine asset generation, the hardware requirements left me with little choice.

GPU: Nvidia RTX PRO 6000 Blackwell (First time seeing this industrial design in person!)

Motherboard: Asus ROG X8706E BTF

Purpose: Local LLM Training/Inference, ComfyUI generation, and Unreal Engine 5 development.

It’s an absolute monster. Loading local models that would usually crash my previous rig happens instantly. I'm still dialing in the drivers and testing ComfyUI pipelines, but early benchmarks are mind-blowing.

For those who have jumped to the Blackwell architecture: Is the price-to-performance jump worth it over just stacking dual RTX 4090s/5090s? I'd Like to hear your thoughts on driver stability for Unreal Engine on this board!

Spent the last few weeks sourcing the specific parts for a dedicated AI production workstation. The goal is a "working" machine for heavy LLM inference and MetaHuman cinematic development—zero cloud, zero bottlenecks.
The core specs on the table:
• GPU: RTX 5090 (32GB VRAM is a game changer for long context)
• CPU: Ryzen 9 9950X 
• RAM: 96GB (Speed over capacity for this specific workflow)
• Storage: 16TB PCIe Gen 5 (Running Ubuntu for the studio environment)
The plan is a clean, BTF-style setup to keep the focus on the production, not the cables. Saturday is build day. Any Ubuntu-specific optimization tips for the 5090 driver stack?