Oct 23, 2023 · Robust monocular depth estimation (MDE) aims at learning a unified model that works across diverse real-world scenes, which is an important ...

Download scientific diagram | Datasets for monocular depth estimation. from publication: Deep Learning-Based Monocular Depth Estimation Methods—A ...

Mar 16, 2024 · Existing monocular depth estimation driving datasets are limited in the number of images and the diversity of driving conditions.

Sep 15, 2021 · Current self-supervised methods for monocular depth estimation are largely based on deeply nested convolutional networks that leverage stereo ...

Jan 12, 2024 · Delving into Multi-illumination Monocular Depth Estimation: A New Dataset and Method ... Abstract: Monocular depth prediction has received ...

Experiments on KITTI and NYU-Depth-v2 datasets demonstrate the effectiveness of each component, its robustness to the use of fewer depth- annotated images, and ...

Apr 15, 2024 · Title:Virtually Enriched NYU Depth V2 Dataset for Monocular Depth Estimation: Do We Need Artificial Augmentation? ; (or arXiv:2404.09469v1 [cs.CV] ...

This comparison focuses on how well methods generalize rather than a quantitative comparison on a specific dataset. This study shows that while monocular depth ...

In other words, it is the process of estimating the distance of objects in a scene from a single camera viewpoint. Monocular depth estimation has various ...

Aug 26, 2023 · 4.1. Datasets ... samples and 654 testing samples , the model is trained on a 50k subset considering inpainted missing depth values and the ...