Existing monocular depth estimation methods have achieved satisfactory performance on wild datasets. However, these methods are usually trained and tested on a ...

Deep Virtual Stereo Odometry: Leveraging Deep Depth. Prediction for Monocular ... Hierarchical normalization for robust monocular depth estimation. 35, 2022 ...

(2022) Hierarchical Normalization for Robust Monocular Depth Estimation Chi Zhang, Wei Yin, Billzb Wang, Gang Yu, BIN FU, Chunhua Shen; (2022) Fully ...

In contrast, the proposed model is robust to such visual pits. The results are best viewed in PDF. In this paper, we propose a novel MDE model referred to as ...

The experiments confirm that mixing data from complementary sources greatly improves monocular depth estimation. Our approach clearly outperforms competing ...

Nov 26, 2022 · This document proposes a hierarchical normalization method called HDN to enable robust monocular depth estimation. HDN normalizes depth maps ...

Based on relative depth estimation,. DGC module can finish per-pixel ground segmentation and estimate a camera height from every ground point. Statistical ...

However, little is known regarding robustness and generalization when it comes to applying monocular depth estimation methods to real-world scenarios where ...

Hierarchical normalization for robust monocular depth estimation. In Adv. Neural Inform. Process. Syst. (NeurIPS), pages 14128–14139,. 2022. 2, 3. [63] Ning ...

Self-supervised monocular depth estimation (SSMDE) aims at predicting the dense depth maps of monocular images, by learning to minimize a photometric loss using ...