As a fundamental task of vision-based perception, 3D occupancy prediction reconstructs 3D
structures of surrounding environments. It provides detailed information for autonomous …

Deep CNNs have achieved impressive improvements for night-time self-supervised depth
estimation form a monocular image. However, the performance degrades considerably …

There has been a recent surge of interest in learning to perceive depth from monocular
videos in an unsupervised fashion. A key challenge in this field is achieving robust and …

Most existing methods often rely on complex models to predict scene depth with high
accuracy, resulting in slow inference that is not conducive to deployment. To better balance …

In recent years, self-supervised monocular depth estimation has been widely applied in
fields such as autonomous driving and robotics. While Convolutional Neural Networks …

In order to solve the problems of unsupervised monocular depth estimation algorithm output
scale blur, inconsistent depth estimation scale between frames, poor depth estimation …