MonoViT. This is the reference PyTorch implementation for training and testing depth estimation models using the method described in. MonoViT: Self ...
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Nov 10, 2023 · Abstract:Self-supervised monocular depth estimation methods aim to be used in critical applications such as autonomous vehicles for ...
Self-supervised monocular depth estimation usually relies on the assumption of a static world during training which is violated by dynamic objects.
Feb 20, 2023 · In this work, we propose two novel ideas to improve self-supervised monocular depth estimation: 1) self-reference distillation and 2) disparity ...
Abstract. Self-supervised monocular depth estimation presents a pow- erful method to obtain 3D scene information from single camera images,.
In this paper, we propose a set of improvements, which together re- sult in both quantitatively and qualitatively improved depth maps compared to competing self ...
May 12, 2021 · In monocular depth estimation, the goal is the generation of pixel-wise estimates (a.k.a. a depth map) of how far each scene element is from the ...
In this paper, we propose a set of improvements, which together re- sult in both quantitatively and qualitatively improved depth maps compared to competing self ...
In this work, we address the problem of jointly esti- mating scene structure and camera motion across RGB im- age sequences using a self-supervised deep network ...
Jul 5, 2024 · The self-supervised monocular depth estimation framework is well-suited for medical images that lack ground-truth depth, such as those from ...
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