A list of recent monocular depth estimation work, inspired by awesome-computer-vision. The list is mainly focusing on recent work after 2020.
High Quality Monocular Depth Estimation via Transfer Learning (arXiv 2018) Ibraheem Alhashim and Peter Wonka
We present DepthFM, a state-of-the-art, versatile, and fast monocular depth estimation model. DepthFM is efficient and can synthesize realistic depth maps ...
An open source monocular depth estimation toolbox based on PyTorch and MMSegmentation v0.16.0. It aims to benchmark MonoDepth methods.
This is the reference PyTorch implementation for training and testing depth estimation models using the method described in MonoViT.
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This work presents Depth Anything, a highly practical solution for robust monocular depth estimation by training on a combination of 1.5M labeled images and ...
Monocular Depth Estimation - Weighted-average prediction from multiple pre-trained depth estimation models - p-ranav/merged_depth.
We propose a method that can generate highly detailed high-resolution depth estimations from a single image.
BTS. From Big to Small: Multi-Scale Local Planar Guidance for Monocular Depth Estimation arXiv · Supplementary material. Video ...
This is a unified codebase for NN-based monocular depth estimation, the framework is based on detectron2 (with a lot of modifications) and supports both ...
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