Thirdly, we introduce the publicly available dataset and the evalua- tion metrics. And we also analysis the properties of these methods and compare their ...

Depth Estimation is the task of measuring the distance of each pixel relative to the camera. Depth is extracted from either monocular (single) or stereo ...

Yu: UniDepth: Universal Monocular Metric Depth Estimation. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2024. 2, 1PNet, 9.46, 1.45, 7.62 ...

Accurate monocular metric depth estimation (MMDE) is crucial to solving downstream tasks in 3D perception and modeling. However, the remarkable accuracy of ...

... metric depth on zero-shot evaluation), arxiv 2024 | github · UniDepth: Universal Monocular Metric Depth Estimation, (universal metric depth estimation; one's ...

May 1, 2023 · Often seen as a challenging problem, monocular depth estimation involves predicting the depth of each pixel given a single input image.

Monocular depth estimation using a single remote sensing image has emerged as a focal point in both remote sensing and computer vision research, ...

[19] proposed a sampling-free strategy for estimating the epistemic uncertainty. Error Diagnostic Measures and Metrics. Error diagnostics have been explored for ...

We present DMD (Diffusion for Metric Depth), a state-of-the-art diffusion model for monocular absolute depth estimation. We make several innovations such as ...

Our results suggest that the standard depth estimation metrics are indeed good indicators of 3D quality, and that they correspond well with human judgements and ...