monocular depth estimation
RSA: Resolving Scale Ambiguities in Monocular Depth Estimators through Language Descriptions
We propose a method for metric-scale monocular depth estimation. Inferring depth from a single image is an ill-posed problem due to the loss of scale from perspective projection during the image formation process.
BetterDepth: Plug-and-Play Diffusion Refiner for Zero-Shot Monocular Depth Estimation
To leverage the complementary merits of both worlds, we propose BetterDepth to achieve geometrically correct affine-invariant MDE while capturing fine details.
DaRF: Boosting Radiance Fields from Sparse Inputs with Monocular Depth Adaptation
Project page is available at https://ku-cvlab.github.io/DaRF/ .
Dynamo-Depth: Fixing Unsupervised Depth Estimation for Dynamical Scenes
Unsupervised monocular depth estimation techniques have demonstrated encouraging results but typically assume that the scene is static.
Supplementary Material IEBins: Iterative Elastic Bins for Monocular Depth Estimation
Table 2 shows a similar performance trend as in NYU-Depth-v2 dataset with increasing number of bins. We report results on keyframes (selected by the ORB-SLAM2) and on all frames of sequences 01-10. The A TE (m) metric is used.
