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Depth Completion

16 papers with code · Computer Vision

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

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

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

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

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

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

DEPTH COMPLETION

Learning Depth with Convolutional Spatial Propagation Network

4 Oct 2018XinJCheng/CSPN

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 STEREO MATCHING

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

31 Jan 2018kujason/ip_basic

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

Sparse and noisy LiDAR completion with RGB guidance anduncertainty

arXiv 2019 wvangansbeke/Sparse-Depth-Completion

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

AUTONOMOUS VEHICLES DEPTH COMPLETION DEPTH ESTIMATION

Sparse and noisy LiDAR completion with RGB guidance and uncertainty

14 Feb 2019wvangansbeke/Sparse-Depth-Completion

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 DEPTH ESTIMATION

Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer Vision

4 Jun 2019fregu856/evaluating_bdl

We therefore accept this task and propose an evaluation framework for predictive uncertainty estimation that is specifically designed to test the robustness required in real-world computer vision applications.

DEPTH COMPLETION SEMANTIC SEGMENTATION

3D LiDAR and Stereo Fusion using Stereo Matching Network with Conditional Cost Volume Normalization

5 Apr 2019zswang666/Stereo-LiDAR-CCVNorm

The complementary characteristics of active and passive depth sensing techniques motivate the fusion of the Li-DAR sensor and stereo camera for improved depth perception.

DEPTH COMPLETION STEREO MATCHING

Confidence Propagation through CNNs for Guided Sparse Depth Regression

5 Nov 2018abdo-eldesokey/nconv

In this paper, we propose an algebraically-constrained normalized convolution layer for CNNs with highly sparse input that has a smaller number of network parameters compared to related work.

AUTONOMOUS DRIVING DEPTH COMPLETION