Mapanything api. This paper introduces MapAnything, a module that .
Mapanything api. For interactive web-based demos, see Interactive Demos. , a collection of depth maps Inference API Relevant source files This document provides comprehensive documentation for the MapAnything inference API, specifically the model. MapAnything is a simple, end-to-end trained transformer model that directly regresses the factored metric 3D geometry of a scene given various types of inputs (images, calibration, poses, or depth). MapAnything leverages a factored representation of multi-view scene geometry, i. We release the complete data processing pipeline, metadata, training scripts, and configs to exactly reproduce the final released version of MapAnything. Sep 17, 2025 · MapAnything is a unified transformer-based model for efficient metric 3D reconstruction from images and optional geometric inputs, outperforming existing methods by simultaneously addressing multiple vision tasks while simplifying the training process. Aug 2, 2018 · MapAnything, the Leader in Location-of-Things software for business, today announced that the company will roll out several API services to provide businesses access to the MapAnything Routing and Optimization engine and other components of the award-winning MapAnything Location-of-Things Platform. The inference API is the primary interface for running 3D reconstruction on input data using pre-trained MapAnything models. MapAnything is the first universal transformer-based backbone that directly regresses metric 3D geometry and camera poses from flexible inputs – including images, camera intrinsics, poses, depth maps, or partial reconstructions – in a single pass. This document specifies the data formats used for input to and output from the MapAnything model inference API. w5fr 7w w4519 tm bpy8td hhsrxf xwla ih ia0nx d2ghn