Monodepth2[ICCV 2019] Monocular depth estimation from a single image
M4DepthOfficial implementation of the network presented in the paper "M4Depth: A motion-based approach for monocular depth estimation on video sequences"
seq2singleVisual place recognition from opposing viewpoints under extreme appearance variations
rectified-features[ECCV 2020] Single image depth prediction allows us to rectify planar surfaces in images and extract view-invariant local features for better feature matching
DE resnet unet hybDepth estimation from RGB images using fully convolutional neural networks.
HoHoNet"HoHoNet: 360 Indoor Holistic Understanding with Latent Horizontal Features" official pytorch implementation.
Indoor-SfMLearner[ECCV'20] Patch-match and Plane-regularization for Unsupervised Indoor Depth Estimation
sc depth plPytorch Lightning Implementation of SC-Depth (V1, V2...) for Unsupervised Monocular Depth Estimation.
OMG Depth FusionProbabilistic depth fusion based on Optimal Mixture of Gaussians for depth cameras
Semantic-Mono-DepthGeometry meets semantics for semi-supervised monocular depth estimation - ACCV 2018
project-defudeRefocus an image just by clicking on it with no additional data
pais-mvsMulti-view stereo image-based 3D reconstruction
DSGNDSGN: Deep Stereo Geometry Network for 3D Object Detection (CVPR 2020)
SGDepth[ECCV 2020] Self-Supervised Monocular Depth Estimation: Solving the Dynamic Object Problem by Semantic Guidance
BridgeDepthFlowBridging Stereo Matching and Optical Flow via Spatiotemporal Correspondence, CVPR 2019
All4DepthSelf-Supervised Depth Estimation on Monocular Sequences
EPCDepth[ICCV 2021] Excavating the Potential Capacity of Self-Supervised Monocular Depth Estimation
EPCEvery Pixel Counts ++: Joint Learning of Geometry and Motion with 3D Holistic Understanding
tf-monodepth2Tensorflow implementation(unofficial) of "Digging into Self-Supervised Monocular Depth Prediction"
monodepthPython ROS depth estimation from RGB image based on code from the paper "High Quality Monocular Depth Estimation via Transfer Learning"