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Found 6 papers, 5 papers with code
Motion Consistency Loss for Monocular Visual Odometry with Attention-Based Deep Learning
Deep learning algorithms have driven expressive progress in many complex tasks.
Transformer-based model for monocular visual odometry: a video understanding approach
In this work, we deal with the monocular visual odometry as a video understanding task to estimate the 6-DoF camera's pose.
An Instance Segmentation Dataset of Yeast Cells in Microstructures
The aim of the dataset and evaluation strategy is to facilitate the development of new cell segmentation approaches.
Dense Prediction Transformer for Scale Estimation in Monocular Visual Odometry
Monocular visual odometry consists of the estimation of the position of an agent through images of a single camera, and it is applied in autonomous vehicles, medical robots, and augmented reality.
Analysis of the performance of U-Net neural networks for the segmentation of living cells
The automated analysis of microscopy images is a challenge in the context of single-cell tracking and quantification.
Multiclass Yeast Segmentation in Microstructured Environments with Deep Learning
Cell segmentation is a major bottleneck in extracting quantitative single-cell information from microscopy data.
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