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Found 2 papers, 1 papers with code
4DRVO-Net: Deep 4D Radar-Visual Odometry Using Multi-Modal and Multi-Scale Adaptive Fusion
We demonstrate the excellent performance of our method and the effectiveness of each module design on both the VoD and in-house datasets.
Toward Hierarchical Self-Supervised Monocular Absolute Depth Estimation for Autonomous Driving Applications
Our contributions are twofold: a) a novel dense connected prediction (DCP) layer is proposed to provide better object-level depth estimation and b) specifically for autonomous driving scenarios, dense geometrical constrains (DGC) is introduced so that precise scale factor can be recovered without additional cost for autonomous vehicles.
Ranked #54 on
Monocular Depth Estimation
on KITTI Eigen split
