Meta AI Researchers Release MapAnything: An End-to-End Transformer Architecture that Directly Regresses Factored, Metric 3D Scene Geometry

Meta AI Researchers Release MapAnything: An End-to-End Transformer Architecture that Directly Regresses Factored, Metric 3D Scene Geometry

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…

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Breaking the data bottleneck: Salesforce’s ProVision speeds multimodal AI training with image scene graphs

Breaking the data bottleneck: Salesforce’s ProVision speeds multimodal AI training with image scene graphs

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More As enterprises around the world double down on their AI projects, the availability of high-quality training data has become a major bottleneck. While the public web has largely been exhausted as a data source, major players…

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