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"Our model leverages the permutation equivariance of the transformer when conditioning on the partial scene, and is trained to be permutation-invariant across object orderings. Our model is trained end-to-end as an autoregressive generative model using only labeled 3D bounding boxes as supervision," wrote the team. "Our formulation allows applying a single trained model to automatic layout synthesis and to a number of interactive scenarios with versatile user input, such as automatic placement of user-provided objects, object suggestion with user-provided constraints, and room completion."
What does the whole thing mean in a few words? Well, you could potentially train such a system using a set of examples, give it an IKEA catalog and make it generate new interiors in a matter of seconds to decorate new spaces. That might sound a bit scary for designers, yes, but these systems still need an initial style.
The official page features the team's paper on the matter, a number of examples, and more. You can learn more about the project and find the code here.
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