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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.
It is shown that a surprisingly simple model, and associated design choices, lead to superior predictions, and together result in both quantitatively and ...
Monocular depth estimators can be trained with various forms of self-supervision from binocular-stereo data to circumvent the need for high-quality laser ...
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