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Monocular Depth Estimation

62 papers with code · Computer Vision
Subtask of Depth Estimation

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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.

MONOCULAR DEPTH ESTIMATION TRANSFER LEARNING

FastDepth: Fast Monocular Depth Estimation on Embedded Systems

8 Mar 2019dwofk/fast-depth

In this paper, we address the problem of fast depth estimation on embedded systems.

MONOCULAR DEPTH ESTIMATION NETWORK PRUNING

Unsupervised Scale-consistent Depth and Ego-motion Learning from Monocular Video

NeurIPS 2019 JiawangBian/SC-SfMLearner-Release

To the best of our knowledge, this is the first work to show that deep networks trained using unlabelled monocular videos can predict globally scale-consistent camera trajectories over a long video sequence.

DEPTH AND CAMERA MOTION MONOCULAR DEPTH ESTIMATION VISUAL ODOMETRY

Semantically-Guided Representation Learning for Self-Supervised Monocular Depth

ICLR 2020 TRI-ML/packnet-sfm

Instead of using semantic labels and proxy losses in a multi-task approach, we propose a new architecture leveraging fixed pretrained semantic segmentation networks to guide self-supervised representation learning via pixel-adaptive convolutions.

MONOCULAR DEPTH ESTIMATION REPRESENTATION LEARNING SELF-SUPERVISED LEARNING SEMANTIC SEGMENTATION

Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer

2 Jul 2019intel-isl/MiDaS

In particular, we propose a robust training objective that is invariant to changes in depth range and scale, advocate the use of principled multi-objective learning to combine data from different sources, and highlight the importance of pretraining encoders on auxiliary tasks.

MONOCULAR DEPTH ESTIMATION

Deep Ordinal Regression Network for Monocular Depth Estimation

CVPR 2018 hufu6371/DORN

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.

MONOCULAR DEPTH ESTIMATION

A General and Adaptive Robust Loss Function

CVPR 2019 jonbarron/robust_loss_pytorch

We present a generalization of the Cauchy/Lorentzian, Geman-McClure, Welsch/Leclerc, generalized Charbonnier, Charbonnier/pseudo-Huber/L1-L2, and L2 loss functions.

IMAGE GENERATION MONOCULAR DEPTH ESTIMATION

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.

MONOCULAR DEPTH ESTIMATION OBJECT DETECTION

Competitive Collaboration: Joint Unsupervised Learning of Depth, Camera Motion, Optical Flow and Motion Segmentation

CVPR 2019 anuragranj/ac

We address the unsupervised learning of several interconnected problems in low-level vision: single view depth prediction, camera motion estimation, optical flow, and segmentation of a video into the static scene and moving regions.

MONOCULAR DEPTH ESTIMATION MOTION ESTIMATION MOTION SEGMENTATION OPTICAL FLOW ESTIMATION