VIDAR: Visual-Inertial Dense Alignment and Reconstruction via a Geometric Foundation Model
VIDAR is a visual-inertial dense reconstruction framework that integrates SVO+IMU odometry with the Depth Anything 3 foundation model. The system uses visual-inertial odometry to provide camera poses, scale, and a consistent world frame, enabling accurate alignment of dense geometry predictions from the foundation model. On the EuRoC dataset, pose injection reduces scale error to about 1% and achieves a mean F@0.10 of 0.463, while a decoupled hybrid approach improves this to 0.676 without relying on ground-truth poses.
Why it matters: VIDAR offers a practical solution for achieving metric dense monocular reconstruction by combining visual-inertial odometry with a geometric foundation model.
Full story at: arXiv Robotics ↗