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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 ...
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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 ...
The RoboDepth Challenge Team is evaluating the robustness of different depth estimation algorithms. MonoViT has achieved the outstanding robustness. KITTI ...
Our self-supervised model,. Monodepth2, produces sharp, high quality depth maps, whether trained with monocular (M), stereo (S), or joint (MS) supervision.
Abstract. Self-supervised monocular depth estimation presents a pow- erful method to obtain 3D scene information from single camera images,.
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 ...
Monocular depth estimation is a method that uses a single camera to estimate pixel-level distance. Even though more specialized hardware devices, such as Lidar ...
Our self-supervised model,. Monodepth2, produces sharp, high quality depth maps, whether trained with monocular (M), stereo (S), or joint (MS) supervision.
Monocular depth estimators can be trained with various forms of self-supervision from binocular-stereo data to circumvent the need for high-quality laser ...
It is shown that a surprisingly simple model, and associated design choices, lead to superior predictions, and together result in both quantitatively and ...
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