Aug 30, 2021 · The goal in monocular depth estimation is to predict the depth value ... depth estimation model with a convnet and simple loss functions.
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Apr 11, 2024 · Loss functions help to quantify the errors between the ground truth and the predicted images, hence enabling a model to optimize and improve its ...
Mar 14, 2020 · Inferring depth information from a single image (monocular depth estimation) is an ill-posed problem. With the rapid development of deep neural ...
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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.
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Loss Functions. We categorize the proposed loss functions for depth esti- mation into direct supervision losses which require ground- truth depth and self ...
For monocular depth estimation, we construct a loss function space of several tens of losses, and propose the loss rebalancing algorithm to utilize the loss.
Mar 15, 2022 · The loss function is effectively used for training a model. In our work, We implement various loss functions based on edge detectors to train a ...
Jan 11, 2023 · Finally, the loss is calculated as the difference between the proposed right image and the recorded right image. At inference, the approach does ...
A standard loss function for depth regression problems considers the difference between the ground truth depth map y and the prediction of the depth regression ...
In this paper, based on the existing methods, we have innovated the loss function and introduced perceptual loss, i.e., we use feedforward neural network to ...