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A list of recent monocular depth estimation work, inspired by awesome-computer-vision. The list is mainly focusing on recent work after 2020. Papers. High ...
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What is the best model for monocular depth estimation?
MiDAS (2019-2022) MiDAS was originally released in 2019 and immediately became the standard. It was one of the first robust models for monocular depth estimation. Since then, the authors have improved its accuracy significantly.
How is depth calculated in monocular vision?
Monocular depth estimation is an underconstrained problem, i.e. geometrically it is impossible to determine the depth of each pixel in the image. However, humans can estimate depth well with a single eye by exploiting cues such as perspective, scaling, and appearance via lighting and occlusion.
What is monocular depth estimation?
Monocular Depth Estimation (MDE), which involves determining depth from a single RGB image, offers numerous advantages, including applications in simultaneous localization and mapping (SLAM), scene comprehension, 3D modeling, robotics, and autonomous driving.
What are the metrics for monocular depth estimation evaluation?
We will leverage sklearn to apply three simple metrics commonly used for monocular depth estimation: root mean squared error (RMSE), peak signal to noise ratio (PSNR), and structural similarity index (SSIM). 💡 Higher PSNR and SSIM scores indicate better predictions, while lower RMSE scores indicate better predictions.
Monocular Depth Estimation is the task of estimating the depth value (distance relative to the camera) of each pixel given a single (monocular) RGB image.
Monocular depth estimation. Monocular depth estimation is a computer vision task that involves predicting the depth information of a scene from a single image.
Self-supervised monocular depth estimation enables robots to learn 3D perception from raw video streams. This scalable approach leverages projective geometry ...
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Boosting Monocular Depth Estimation Models to High-Resolution via ...
yaksoy.github.io › highresdepth
We propose a method that can generate highly detailed high-resolution depth estimations from a single image. Our method is based on optimizing the performance ...
To the best of the authors' knowledge, this paper demonstrates real-time monocular depth estimation using a deep neural network with the highest throughput on ...
May 18, 2022 · Most works in self-supervised monocular depth estimation focus on only two of the three components required to use geometry as inductive biases ...
Mar 20, 2024 · Monocular depth estimation, the prediction of distance in 3D space from a 2D image. The “ill posed and inherently ambiguous problem”, ...
An open API service indexing awesome lists of open source software. awesome-monocular-3D-reconstruction. A list of papers about monocular reconstruction ( ...
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