Oct 18, 2022 · In this paper, we propose a novel multi-scale depth normalization method that hierarchically normalizes the depth representations based on ...

In this paper, we address monocular depth estimation with deep neural networks. To enable training of deep monocular estimation models with various sources.

Oct 31, 2022 · The authors introduce a novel strategy for monocular depth estimation that focuses on both global structure and fine-grained details. Their ...

Oct 18, 2022 · We propose a hierarchical depth normalization strategy to improve the learning of deep monocular estimation models. • We present two ...

ABSTRACT · References

By default, the inference resizes the height of input images to the size of a model to fit into the encoder. This size is given by the numbers in the model ...

Jul 26, 2023 · Bibliographic details on Hierarchical Normalization for Robust Monocular Depth Estimation.

In this paper, we address monocular depth estimation with deep neuralnetworks. To enable training of deep monocular estimation models with varioussources of ...

Abstract. This paper proposes a hierarchical loss for monocular depth estimation, which measures the differences between the prediction and ground truth in  ...

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.