SAM 3D - Meta open source 3D reconstruction model series

What is SAM 3D?

SAM 3D is a 3D reconstruction model based on the SAM series launched by Meta, including two branches, SAM 3D Objects and SAM 3D Body. SAM 3D Objects can generate interactive 3D object models from a single photo, supporting complex scenes and occlusion processing; SAM 3D Body focuses on human body reconstruction, accurately reproducing poses, shapes, and key points, and is suitable for virtual human and animation production. The models use a unified architecture to integrate tasks such as 2D segmentation and depth prediction, and the generalization ability of real scenes is greatly improved by an innovative data engine, and the related code and experience platform have been opened.

Features of SAM 3D

• Powerful 3D reconstruction capabilities: SAM 3D consists of two models, SAM 3D Objects and SAM 3D Body. SAM 3D Objects reconstructs detailed 3D shapes, textures, and scene layouts of objects from a single still photo, and performs well even in complex situations such as small objects, side views, and occlusions. It has a win rate of at least 5 to 1 in human preference tests.
• Accurate human posture and shape estimation: SAM 3D Body focuses on accurately estimating the 3D pose and shape of the human body from a single image, maintaining high quality performance even in complex situations such as multi-person scenes, unusual poses or occlusions. Interactive inputs such as segmentation masks and 2D keypoints are supported, with which the user can guide and control the model's predictions.
• Efficient data annotation engine: To train SAM 3D, Meta built a powerful data annotation engine that combines AI annotation and human annotation to significantly improve annotation efficiency. It enables the model to be trained based on large-scale high-quality data, outperforming previous models in multiple 3D benchmark tests.
• Open model weights and inference codes: Meta has open-sourced the model weighting and inference code for SAM 3D for easy use and further research by developers and researchers.
• Easy-to-use experience platform: Meta has launched the Segment Anything Playground platform, which allows ordinary users to upload images and experience SAM 3D's 3D reconstruction and segmentation capabilities without a technical background.

Core Benefits of SAM 3D

• Robustness driven by high quality data: To train SAM 3D, Meta constructed a high-quality training dataset containing approximately 8 million images, allowing it to cope with occlusions, rare poses, and diverse clothing. This use of large-scale, high-quality data enabled SAM 3D to outperform previous models in several 3D benchmark tests.
• Innovative data annotation engine: Meta builds a scalable data engine that combines AI labeling and human labeling to significantly improve labeling efficiency. This enables models to be trained on large-scale diverse data, thus excelling in complex visual tasks.
• Open model weights and inference codes: Meta has open-sourced the model weighting and inference code for SAM 3D for easy use and further research by developers and researchers.

What is the official website for SAM 3D

• Project website:: https://ai.meta.com/sam3d/
• GitHub repository::
  • SAM 3D Body: https://github.com/facebookresearch/sam-3d-body
  • SAM 3D Objects:: https://github.com/facebookresearch/sam-3d-objects
• Technical Report:: https://ai.meta.com/research/publications/sam-3d-body-robust-full-body-human-mesh-recovery/

Who SAM 3D is for

• 3D modeler and animator: It can quickly generate high-quality 3D models from 2D images, saving modeling time and cost and improving work efficiency.
• game developer: Used to create realistic 3D game scenes and characters to enhance the visual effect and immersion of the game.
• Virtual Reality (VR) and Augmented Reality (AR) Developers: Rapidly generate 3D content to enhance the realism and interactivity of virtual environments.
• E-commerce and advertising industry practitioners: Create 3D models of products to provide a more intuitive product display, enhancing user experience and purchase intent.
• Researchers and academic researchers: For research in computer vision, 3D reconstruction, human pose estimation and other fields to promote the development of related technologies.
• General Users and Enthusiasts: Through the Segment Anything Playground platform, 3D reconstruction and segmentation can be experienced without specialized skills for personal creativity and entertainment.