DME: Unveiling the Bias for Better Generalized Monocular Depth Estimation (original) (raw)

Progress and Proposals: A Case Study of Monocular Depth Estimation

Khalil Sarwari

2021

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Learn to Adapt for Monocular Depth Estimation

Gary Yen

Cornell University - arXiv, 2022

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Deep Classification Network for Monocular Depth Estimation

Azeez Oluwafemi

2019

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From 2D to 3D: Re-thinking Benchmarking of Monocular Depth Prediction

evin Ornek

ArXiv, 2022

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Monocular Depth Estimation Using Deep Learning: A Review

Domenec Puig

Sensors

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MobileXNet: An Efficient Convolutional Neural Network for Monocular Depth Estimation

Xingshuai Dong

IEEE Transactions on Intelligent Transportation Systems

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CNN Based Monocular Depth Estimation

Hima Valiveti

E3S Web of Conferences, 2021

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NVS-MonoDepth: Improving Monocular Depth Prediction with Novel View Synthesis

Martin R. Oswald

2021 International Conference on 3D Vision (3DV), 2021

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GCNDepth: Self-supervised monocular depth estimation based on graph convolutional network

Hatem A . Rashwan

Neurocomputing, 2023

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Object-Aware Monocular Depth Prediction With Instance Convolutions

evin Ornek

IEEE Robotics and Automation Letters, 2022

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RealMonoDepth: Self-Supervised Monocular Depth Estimation for General Scenes

Armin Mustafa

ArXiv, 2020

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The Monocular Depth Estimation Challenge

Jaime Spencer

Cornell University - arXiv, 2022

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Monocular Depth Estimation using Transfer learning-An Overview

Chaitanya Duggineni

E3S Web of Conferences

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A Review of Benchmark Datasets and Training Loss Functions in Neural Depth Estimation

Shubhajit Basak

IEEE Access, 2021

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Learning Monocular Depth by Distilling Cross-Domain Stereo Networks

Shuai Yi

Computer Vision – ECCV 2018, 2018

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Sparse Auxiliary Networks for Unified Monocular Depth Prediction and Completion

Vitor Guizilini

2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

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DeFeat-Net: General Monocular Depth via Simultaneous Unsupervised Representation Learning

Simon Hadfield

2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

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Toward Domain Independence for Learning-Based Monocular Depth Estimation

Paolo Valigi

IEEE Robotics and Automation Letters, 2017

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Monocular Depth Estimation Using State-of-the-art Algorithms: A Review

Tea Dogandzic

Proceedings of the International Scientific Conference - Sinteza 2023, 2023

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Guiding Monocular Depth Estimation Using Depth-Attention Volume

Lam Huynh

Computer Vision – ECCV 2020, 2020

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X-Distill: Improving Self-Supervised Monocular Depth via Cross-Task Distillation

shubhankar borse

2021

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LocalBins: Improving Depth Estimation by Learning Local Distributions

Shariq Farooq

arXiv (Cornell University), 2022

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Robust Semi-Supervised Monocular Depth Estimation with Reprojected Distances

Vitor Guizilini

2019

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Ing for Self-Supervised Monocular Depth

Vitor Guizilini

2020

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Improving Depth Estimation using Location Information

Hazem Abbas

2021 16th International Conference on Computer Engineering and Systems (ICCES), 2021

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SUW-Learn: Joint Supervised, Unsupervised, Weakly Supervised Deep Learning for Monocular Depth Estimation

Aman Raj

2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

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ADAADepth: Adapting Data Augmentation and Attention for Self-Supervised Monocular Depth Estimation

Vinay Kaushik

IEEE Robotics and Automation Letters, 2021

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The Temporal Opportunist: Self-Supervised Multi-Frame Monocular Depth

Jamie Watson

2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021

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Learning Single Camera Depth Estimation Using Dual-Pixels

Sameer Ansari

2019 IEEE/CVF International Conference on Computer Vision (ICCV), 2019

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A Lightweight Self-Supervised Training Framework for Monocular Depth Estimation

Shan Du

ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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On Regression Losses for Deep Depth Estimation

Marcela Carvalho E.

2018 25th IEEE International Conference on Image Processing (ICIP), 2018

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One scalar is all you need -- absolute depth estimation using monocular self-supervision

Ofer M

arXiv (Cornell University), 2023

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Single image depth estimation: An overview

Damien Duff

Digital Signal Processing, 2022

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Self-Supervised Correlational Monocular Depth Estimation using ResVGG Network

Kuo Shiuan Peng

Proceedings of The 7th International Conference on Intelligent Systems and Image Processing 2019

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Multi-Frame Self-Supervised Depth with Transformers

Vitor Guizilini

ArXiv, 2022

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