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Code for robust monocular depth estimation described in "Ranftl et. al., Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot ...
This is the official implementation of the paper: Monocular Depth Prediction Through Continuous 3D Loss. See arXiv version.
Unified benchmark. Provide a unified benchmark toolbox for various depth estimation methods. Modular design. Depth estimation frameworks are decomposed into ...
Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer. This repository contains code to compute depth from a single ...
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 ...
This directory contains depth map of background-foreground images. These are called background-foreground depth maps. Image Size: 224x224x1; Number of Images: ...
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Monocular depth estimation is a challenging task that predicts the pixel-wise depth from a single 2D image. We propose DiffusionDepth, a new approach that ...
First, we create a rainy version of the KITTI dataset using a GAN. We download CycleGAN from the repository CycleGAN. git clone https://github.com/junyanz/ ...
Monocular depth estimation from ArgoAI's Lidar based Depth dataset - Depth predictions up-to 200m - TilakD/Monocular-Depth-Estimation-Argoverse.
Ibraheem Alhashim and Peter Wonka. [Update] Our latest method with better performance can be found here AdaBins. Offical Keras (TensorFlow) implementaiton.