Depth Completion

34 papers with code • 5 benchmarks • 4 datasets

The Depth Completion task is a sub-problem of depth estimation. Instead of knowing nothing about the scene, the Depth Completion task has strong priors on scene depth. The goal of Depth Completion is to fill in the depth on pixels where there is no valid depth. The pixels where the input sparse depth map has a valid value should remain unchanged during the process.

Source: LiStereo: Generate Dense Depth Maps from LIDAR and Stereo Imagery

Greatest papers with code

Self-supervised Sparse-to-Dense: Self-supervised Depth Completion from LiDAR and Monocular Camera

fangchangma/self-supervised-depth-completion 1 Jul 2018

Depth completion, the technique of estimating a dense depth image from sparse depth measurements, has a variety of applications in robotics and autonomous driving.

Autonomous Driving Depth Completion

Learning Depth with Convolutional Spatial Propagation Network

XinJCheng/CSPN 4 Oct 2018

In this paper, we propose a simple yet effective convolutional spatial propagation network (CSPN) to learn the affinity matrix for various depth estimation tasks.

Depth Completion Depth Estimation +2

Parse Geometry from a Line: Monocular Depth Estimation with Partial Laser Observation

fangchangma/sparse-to-dense.pytorch 17 Oct 2016

Many standard robotic platforms are equipped with at least a fixed 2D laser range finder and a monocular camera.

Depth Completion

Sparse and noisy LiDAR completion with RGB guidance anduncertainty

wvangansbeke/Sparse-Depth-Completion arXiv 2019

For autonomous vehicles and robotics the use of LiDAR is indispensable in order to achieve precise depth predictions.

Autonomous Vehicles Depth Completion +1

Sparse and noisy LiDAR completion with RGB guidance and uncertainty

wvangansbeke/Sparse-Depth-Completion 14 Feb 2019

However, we additionally propose a fusion method with RGB guidance from a monocular camera in order to leverage object information and to correct mistakes in the sparse input.

Autonomous Vehicles Depth Completion +1

In Defense of Classical Image Processing: Fast Depth Completion on the CPU

kujason/ip_basic 31 Jan 2018

With the rise of data driven deep neural networks as a realization of universal function approximators, most research on computer vision problems has moved away from hand crafted classical image processing algorithms.

Depth Completion

DeepLiDAR: Deep Surface Normal Guided Depth Prediction for Outdoor Scene from Sparse LiDAR Data and Single Color Image

JiaxiongQ/DeepLiDAR CVPR 2019

In this paper, we propose a deep learning architecture that produces accurate dense depth for the outdoor scene from a single color image and a sparse depth.

Depth Completion Depth Estimation

ClearGrasp: 3D Shape Estimation of Transparent Objects for Manipulation

Shreeyak/cleargrasp 6 Oct 2019

To address these challenges, we present ClearGrasp -- a deep learning approach for estimating accurate 3D geometry of transparent objects from a single RGB-D image for robotic manipulation.

Depth Completion Monocular Depth Estimation +3

Non-Local Spatial Propagation Network for Depth Completion

zzangjinsun/NLSPN_ECCV20 ECCV 2020

In this paper, we propose a robust and efficient end-to-end non-local spatial propagation network for depth completion.

Depth Completion Stereo-LiDAR Fusion