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6 days ago · A self-supervised framework [57] is proposed to compute photometric consistency between monocular frames, facilitating joint training of a single-frame depth ...
20 hours ago · Temporal 3D object detection solutions focus on coarse-grained predictions at region-level [27, 25] , while video depth estimation methods [28, 5] aim to ...
2 days ago · Hierarchical Normalization for Robust Monocular Depth Estimation. In Advances in Neural Information Processing Systems Vol. 35. USA: Neural information ...
1 day ago · This method can optimize the displacement field without the need for training, and can achieve both high spatial resolution and high measurement resolution.
1 day ago · It is calculated as the sum of binary cross-entropy losses between predicted depth values (\hat{y}i) and ground truth labels (y_i), normalized by the number of ...
5 days ago · In this paper, we propose to learn geometry-guided depth estimation with projective modeling to advance monocular 3D object detection. Ranked #10 on Monocular ...
6 days ago · Real Time Monocular Vehicle Velocity Estimation Using Synthetic Data, R. ... Instance Normalization: The Missing Ingredient for Fast Stylization, D.
4 days ago · The fundamental deep learning process consists of constructing multiple deep layers to create a neural network, identifying optimal parameters for each layer, ...
7 days ago · In this paper, we propose an ACDNet based on the adaptively combined dilated convolution to predict the dense depth map for a monocular panoramic image.
Deep learning approach for cable partial discharge pattern identification
link.springer.com › article
1 day ago · This method allows for robust analysis of PD patterns in both the time and frequency domains, enhancing diagnostic capabilities.
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