SAM 3D Objects represents a new approach to tackling robust, visually grounded 3D reconstruction and object pose estimation from a single natural image. This model reconstructs detailed 3D shapes, textures, and layouts of objects from everyday images, making it easy to precisely manipulate individual objects in a reconstructed 3D scene. SAM 3D Objects significantly outperforms existing methods, generalizing well across many types of images and supporting dense scene reconstructions. In head-to-head human preference tests, it achieves at least a 5:1 win rate over other leading models.
SAM 3D Body addresses the need for accurate 3D human pose and shape estimations from a single image — even in complex situations that involve unusual postures, blocked portions of the image, or multiple people. This model delivers accurate and robust 3D human pose and shape estimation by leveraging large-scale, high-quality data and a robust training strategy. SAM 3D Body stands out for its step change in accuracy and robustness, outperforming previous models on multiple 3D benchmarks. With this release, we’re also sharing MHR, the parametric human model enabling Meta’s technologies like Codec Avatars, under a permissive commercial license.
