Seems like video game engines and the like would be useful ways to get lots of 3d models to corresponding point cloud data. What's the blocker to doing that? The models shown on that page look like 3d graphics circa 2000's or earlier.
Without knowing a dang thing about AI, it feels like the problem moreso lies in:
1. Math related to topology: vertices, faces, edges, tri vs quad etc
2. Different topologies for the same object are better for different use cases. Rendering, skinning, morphing, physics etc all have different optimal topologies, and the definition of optimal varies based on workflow and scene specifics or even the human who has skills based on certain topological preferences. In other words, I'm not sure how much of 3D workflows are standardized even -- getting the topological data for workflows is no easy task, and it's not super usable until the model output can plug right into a workflow and the existing DCC ecosystem.
text2img generates a static asset, text2mesh is far more interesting beyond just the static rendering part which is where mesh topology becomes a big sticking point.
I believe there are three problems:
* There isn't software that generates point clouds from video games. This should be solvable but AFAIK hasn't been done yet.
* The diversity of models in video games is much lower than the real world
* Games use a bunch of techniques to reduce the poly count while making assets look like they are high poly (eg texture mapping). It's unclear what should be generated here.
Take a look at the field of NeRFs (Neural Radiance Fields: https://datagen.tech/guides/synthetic-data/neural-radiance-f...) for more on this subject.