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# Monocular Depth Estimation Edit

28 papers with code · Computer Vision

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# Unsupervised Monocular Depth Estimation with Left-Right Consistency

Learning based methods have shown very promising results for the task of depth estimation in single images.

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# On the Importance of Stereo for Accurate Depth Estimation: An Efficient Semi-Supervised Deep Neural Network Approach

26 Mar 2018NVIDIA-AI-IOT/redtail

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.

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# Digging Into Self-Supervised Monocular Depth Estimation

4 Jun 2018nianticlabs/monodepth2

Per-pixel ground-truth depth data is challenging to acquire at scale.

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# High Quality Monocular Depth Estimation via Transfer Learning

31 Dec 2018ialhashim/DenseDepth

Accurate depth estimation from images is a fundamental task in many applications including scene understanding and reconstruction.

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# Unsupervised Learning of Monocular Depth Estimation and Visual Odometry with Deep Feature Reconstruction

Despite learning based methods showing promising results in single view depth estimation and visual odometry, most existing approaches treat the tasks in a supervised manner.

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# 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.

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# Fast Robust Monocular Depth Estimation for Obstacle Detection with Fully Convolutional Networks

21 Jul 2016fangchangma/sparse-to-dense.pytorch

We propose a novel appearance-based Object Detection system that is able to detect obstacles at very long range and at a very high speed (~300Hz), without making assumptions on the type of motion.

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# Deep Ordinal Regression Network for Monocular Depth Estimation

These methods model depth estimation as a regression problem and train the regression networks by minimizing mean squared error, which suffers from slow convergence and unsatisfactory local solutions.

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# Revisiting Single Image Depth Estimation: Toward Higher Resolution Maps with Accurate Object Boundaries

23 Mar 2018JunjH/Revisiting_Single_Depth_Estimation

Experimental results show that these two improvements enable to attain higher accuracy than the current state-of-the-arts, which is given by finer resolution reconstruction, for example, with small objects and object boundaries.

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# Structured Attention Guided Convolutional Neural Fields for Monocular Depth Estimation

Recent works have shown the benefit of integrating Conditional Random Fields (CRFs) models into deep architectures for improving pixel-level prediction tasks.

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