Depth Estimation
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Greatest papers with code
Depth Prediction Without the Sensors: Leveraging Structure for Unsupervised Learning from Monocular Videos
Models and examples built with TensorFlow
Unsupervised Monocular Depth Estimation with Left-Right Consistency
CVPR 2017
• mrharicot/monodepth
• 
Learning based methods have shown very promising results for the task of depth estimation in single images.
Deeper Depth Prediction with Fully Convolutional Residual Networks
• iro-cp/FCRN-DepthPrediction
•
This paper addresses the problem of estimating the depth map of a scene given a single RGB image.
On the Importance of Stereo for Accurate Depth Estimation: An Efficient Semi-Supervised Deep Neural Network Approach
Despite the progress on monocular depth estimation in recent years, we show that the gap between monocular and stereo depth accuracy remains large$-$a particularly relevant result due to the prevalent reliance upon monocular cameras by vehicles that are expected to be self-driving.
Pyramid Stereo Matching Network
CVPR 2018
• JiaRenChang/PSMNet
• 
The spatial pyramid pooling module takes advantage of the capacity of global context information by aggregating context in different scales and locations to form a cost volume.
gvnn: Neural Network Library for Geometric Computer Vision
• ankurhanda/gvnn
• 
We introduce gvnn, a neural network library in Torch aimed towards bridging the gap between classic geometric computer vision and deep learning.
Towards 3D Human Pose Estimation in the Wild: a Weakly-supervised Approach
ICCV 2017
• xingyizhou/pytorch-pose-hg-3d
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We propose a weakly-supervised transfer learning method that uses mixed 2D and 3D labels in a unified deep neutral network that presents two-stage cascaded structure.
#4 best model for
3D Human Pose Estimation
on Human3.6M
Real-Time Joint Semantic Segmentation and Depth Estimation Using Asymmetric Annotations
• DrSleep/light-weight-refinenet
•
Deployment of deep learning models in robotics as sensory information extractors can be a daunting task to handle, even using generic GPU cards.
DEPTH ESTIMATION REAL-TIME SEMANTIC SEGMENTATION SURFACE NORMALS ESTIMATION
Sparse-to-Dense: Depth Prediction from Sparse Depth Samples and a Single Image
• fangchangma/sparse-to-dense
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We consider the problem of dense depth prediction from a sparse set of depth measurements and a single RGB image.
DEPTH ESTIMATION SIMULTANEOUS LOCALIZATION AND MAPPING SUPER RESOLUTION
Parse Geometry from a Line: Monocular Depth Estimation with Partial Laser Observation
• fangchangma/sparse-to-dense
•
Many standard robotic platforms are equipped with at least a fixed 2D laser range finder and a monocular camera.