Monocular depth estimation based on deep learning: An overview
Depth information is important for autonomous systems to perceive environments and
estimate their own state. Traditional depth estimation methods, like structure from motion …
estimate their own state. Traditional depth estimation methods, like structure from motion …
Monocular depth estimation using deep learning: A review
In current decades, significant advancements in robotics engineering and autonomous
vehicles have improved the requirement for precise depth measurements. Depth estimation …
vehicles have improved the requirement for precise depth measurements. Depth estimation …
The temporal opportunist: Self-supervised multi-frame monocular depth
Self-supervised monocular depth estimation networks are trained to predict scene depth
using nearby frames as a supervision signal during training. However, for many …
using nearby frames as a supervision signal during training. However, for many …
Self-supervised monocular depth estimation: Solving the dynamic object problem by semantic guidance
Self-supervised monocular depth estimation presents a powerful method to obtain 3D scene
information from single camera images, which is trainable on arbitrary image sequences …
information from single camera images, which is trainable on arbitrary image sequences …
Unsupervised scale-consistent depth and ego-motion learning from monocular video
Recent work has shown that CNN-based depth and ego-motion estimators can be learned
using unlabelled monocular videos. However, the performance is limited by unidentified …
using unlabelled monocular videos. However, the performance is limited by unidentified …
Digging into self-supervised monocular depth estimation
Per-pixel ground-truth depth data is challenging to acquire at scale. To overcome this
limitation, self-supervised learning has emerged as a promising alternative for training …
limitation, self-supervised learning has emerged as a promising alternative for training …
Depth from videos in the wild: Unsupervised monocular depth learning from unknown cameras
We present a novel method for simultaneous learning of depth, egomotion, object motion,
and camera intrinsics from monocular videos, using only consistency across neighboring …
and camera intrinsics from monocular videos, using only consistency across neighboring …
Towards real-time monocular depth estimation for robotics: A survey
As an essential component for many autonomous driving and robotic activities such as ego-
motion estimation, obstacle avoidance and scene understanding, monocular depth …
motion estimation, obstacle avoidance and scene understanding, monocular depth …
Deep learning-based depth estimation methods from monocular image and videos: A comprehensive survey
Estimating depth from single RGB images and videos is of widespread interest due to its
applications in many areas, including autonomous driving, 3D reconstruction, digital …
applications in many areas, including autonomous driving, 3D reconstruction, digital …
[HTML][HTML] Gcndepth: Self-supervised monocular depth estimation based on graph convolutional network
Depth estimation is a challenging task of 3D reconstruction to enhance the accuracy sensing
of environment awareness. This work brings a new solution with improvements, which …
of environment awareness. This work brings a new solution with improvements, which …