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🧊 3D Generation

SAM 3 - 3D Align

Reconstruct full 3D scenes with people and objects aligned in unified space.

Example Output

Output

Generated

Try SAM 3 - 3D Align

Fill in the parameters below and click "Generate" to try this model

URL of the original image used for depth estimation *

URL of the original image used for depth estimation

URL of the SAM-3D Body mesh file (.ply or .glb) to align *

URL of the SAM-3D Body mesh file (.ply or .glb) to align

Optional URL of the human mask image. If not provided, uses full image

Optional URL of SAM-3D Object mesh (.glb) to create combined scene

Focal length from SAM-3D Body metadata. Auto-estimated if not provided

Your inputs will be saved and ready after sign in

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About SAM 3 - 3D Align

SAM 3 - 3D Align is an advanced AI-powered model designed for seamless full-scene 3D reconstructions, expertly placing both human bodies and objects within a unified, context-rich 3D space. Leveraging state-of-the-art depth estimation and mesh alignment technology, this model transforms 2D images and mesh data into highly accurate 3D visualizations, making it an essential tool for industries that require precise spatial understanding and immersive scene creation. At its core, SAM 3 - 3D Align processes an input image along with body and object mesh files (in .ply or .glb formats), automatically estimating or accepting provided focal length data to achieve lifelike proportions and placements. The model can utilize an optional human mask to improve segmentation or work with the full image when necessary. By aligning body meshes with object meshes in a shared 3D context, it enables the creation of comprehensive scenes where the relationships between people and objects are spatially accurate and visually coherent. This powerful AI model is ideal for 3D artists, VR/AR developers, animators, game designers, and professionals in architecture or robotics who seek to generate or analyze realistic digital environments. Whether you're reconstructing a physical space, preparing assets for virtual staging, or developing interactive simulations, SAM 3 - 3D Align offers a streamlined workflow that delivers reliable, high-quality outputs in multiple formats, including PLY, GLB, visualizations, metadata, and combined scene files. Key capabilities include automated depth estimation, flexible input handling via URLs or file uploads, and fast processing times (typically 30-60 seconds per scene). The model's robust mesh alignment ensures that human and object elements maintain accurate spatial relationships, crucial for applications like animation, robotics training, scene understanding, and digital twin creation. With support for optional body masks and object meshes, users have granular control over the scene composition, enhancing both the accuracy and versatility of their 3D projects. Supported by a user-friendly credit-based platform, SAM 3 - 3D Align is accessible to professionals and creators looking to elevate their 3D workflows with AI-driven automation. Explore new possibilities in digital content creation, spatial analysis, and immersive visualization, all powered by cutting-edge 3D scene alignment technology.

✨ Key Features

Performs full 3D scene reconstruction by aligning body and object meshes within a unified spatial context.

Accepts input images and mesh files via URL or direct file upload, supporting .ply and .glb formats.

Automatically estimates the camera's focal length for realistic depth representation, with manual override available.

Supports optional human mask images for enhanced segmentation and precision.

Delivers multiple output formats including aligned body PLY, GLB mesh, combined scene GLB, visualization, and metadata.

Processes each scene quickly, typically within 30-60 seconds, streamlining 3D content workflows.

Flexible integration for various 3D generation, visualization, and analysis applications.

💡 Use Cases

Creating immersive 3D scenes for virtual reality (VR) and augmented reality (AR) experiences.

Automating the alignment of human and object meshes for game asset preparation.

Generating precise digital twins for architectural visualization and spatial analysis.

Assisting robotics development through accurate spatial mapping of environments.

Enhancing animation pipelines with realistic human-object spatial relationships.

Facilitating rapid prototyping of interactive 3D simulations.

Supporting research in computer vision and scene understanding.

🎯

Best For

3D artists, animators, VR/AR developers, game designers, and professionals in architecture, robotics, or digital content creation.

👍 Pros

Delivers highly accurate 3D alignment for both human and object meshes.
Supports a wide range of file formats and flexible input methods.
Fast processing enables efficient project workflows.
Offers multiple output types for diverse 3D applications.
Automated depth and focal length estimation reduces manual setup.
Enables detailed, context-aware scene reconstructions ideal for professional use.

⚠️ Considerations

Requires high-quality input images and meshes for best results.
Optional features (like human masks) may need additional data preparation.
Output quality can depend on the accuracy of provided mesh files.
Currently optimized for specific mesh formats (.ply, .glb) only.

📚 How to Use SAM 3 - 3D Align

Prepare your source image and ensure you have compatible body mesh and (optionally) object mesh files in .ply or .glb format.

Upload or provide URLs for the image and mesh files in the model interface.

Optionally, upload a human mask image to improve segmentation, or leave blank to use the full image.

Enter the camera focal length if known, or allow the model to auto-estimate it.

Submit your inputs and wait for processing (typically 30-60 seconds).

Download the aligned mesh outputs, visualizations, and combined scene files for use in your 3D projects.

Frequently Asked Questions

🏷️ Related Keywords

3D scene alignment 3D reconstruction mesh alignment AI 3D generation body mesh alignment object mesh integration virtual reality scene understanding digital twin spatial analysis

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