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Found 3 papers, 1 papers with code
Boosting Unsupervised Segmentation Learning
We present two practical improvement techniques for unsupervised segmentation learning.
Generative Adversarial Learning via Kernel Density Discrimination
We show a boost in the quality of generated samples with respect to FID from 10% to 40% compared to the baseline.
SelfVIO: Self-Supervised Deep Monocular Visual-Inertial Odometry and Depth Estimation
In the last decade, numerous supervised deep learning approaches requiring large amounts of labeled data have been proposed for visual-inertial odometry (VIO) and depth map estimation.
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