Unsupervised Monocular Depth Estimation
35 papers with code • 5 benchmarks • 4 datasets
Benchmarks
These leaderboards are used to track progress in Unsupervised Monocular Depth Estimation
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Cityscapes
KITTI
KITTI-C
CamlessVideosFromTheWild
Most implemented papers
Unsupervised Monocular Depth Estimation with Left-Right Consistency
mrharicot/monodepth
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CVPR 2017
Learning based methods have shown very promising results for the task of depth estimation in single images.
Digging Into Self-Supervised Monocular Depth Estimation
Per-pixel ground-truth depth data is challenging to acquire at scale.
Depth Prediction Without the Sensors: Leveraging Structure for Unsupervised Learning from Monocular Videos
Models and examples built with TensorFlow
Unsupervised Monocular Depth Learning in Dynamic Scenes
google-research/google-research
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We present a method for jointly training the estimation of depth, ego-motion, and a dense 3D translation field of objects relative to the scene, with monocular photometric consistency being the sole source of supervision.
Towards real-time unsupervised monocular depth estimation on CPU
mattpoggi/pydnet
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To tackle this issue, in this paper we propose a novel architecture capable to quickly infer an accurate depth map on a CPU, even of an embedded system, using a pyramid of features extracted from a single input image.
Depth from Videos in the Wild: Unsupervised Monocular Depth Learning from Unknown Cameras
google-research/google-research
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ICCV 2019
We present a novel method for simultaneous learning of depth, egomotion, object motion, and camera intrinsics from monocular videos, using only consistency across neighboring video frames as supervision signal.
A General and Adaptive Robust Loss Function
google-research/google-research
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CVPR 2019
We present a generalization of the Cauchy/Lorentzian, Geman-McClure, Welsch/Leclerc, generalized Charbonnier, Charbonnier/pseudo-Huber/L1-L2, and L2 loss functions.
SC-DepthV3: Robust Self-supervised Monocular Depth Estimation for Dynamic Scenes
Self-supervised monocular depth estimation has shown impressive results in static scenes.
Dual CNN Models for Unsupervised Monocular Depth Estimation
ishmav16/Dual-CNN-Models-for-Unsupervised-Monocular-Depth-Estimation
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The unsupervised depth estimation is the recent trend by utilizing the binocular stereo images to get rid of depth map ground truth.
Learning monocular depth estimation with unsupervised trinocular assumptions
mattpoggi/3net
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Obtaining accurate depth measurements out of a single image represents a fascinating solution to 3D sensing.
