A team of researchers from Meta Reality Labs and Carnegie Mellon University has introduced MapAnything, an end-to-end transformer architecture that directly regresses factored metric 3D scene geometry from images and optional sensor inputs. Released under Apache 2.0 with full training and benchmarking code, MapAnything advances beyond specialist pipelines by supporting over 12 distinct 3D vision […]
The post Meta AI Researchers Release MapAnything: An End-to-End Transformer Architecture that Directly Regresses Factored, Metric 3D Scene Geometry appeared first on MarkTechPost.