HiP3Rs/HiP3R

What it solves

HiP3R addresses the challenge of creating accurate 3D reconstructions from long video sequences. By breaking long sequences into manageable, overlapping chunks and using hierarchical pose graphs, it maintains spatial consistency and refines camera positions over extended durations.

How it works

The system processes video input by dividing it into chunks—60 frames for the VGGT-Omega backend or 120 frames for LingBot-MAP. It uses SALAD for loop retrieval to identify when the camera revisits a location, which helps align the chunks correctly. It then performs keyframe pose refinement to ensure the final 3D reconstruction is smooth and accurate.

Who it’s for

This tool is designed for researchers and developers working on computer vision and 3D scene reconstruction who need to process long-duration video data into structured camera poses and point clouds.

Highlights

• Supports multiple backend models including VGGT-Omega and LingBot-MAP.
• Integrates SALAD for robust loop retrieval to improve alignment.
• Outputs standard camera-to-world matrices and intrinsic matrices for easy integration with other tools.
• Provides modular chunk-based data storage for efficient handling of large reconstructions.