Matteo Poggi

IEEE Trans. Pattern Anal. Mach. Intell., January, 2024

How NeRFs and 3D Gaussian Splatting are Reshaping SLAM: a Survey.

[BibT_eX]

[DOI]

CoRR, 2024

Range-Agnostic Multi-View Depth Estimation With Keyframe Selection.

[BibT_eX]

[DOI]

CoRR, 2024

2023

Depth super-resolution from explicit and implicit high-frequency features.

[BibT_eX]

[DOI]

Comput. Vis. Image Underst., December, 2023

Self-supervised depth super-resolution with contrastive multiview pre-training.

[BibT_eX]

[DOI]

Neural Networks, November, 2023

Depth Restoration in Under-Display Time-of-Flight Imaging.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., May, 2023

Revisiting Depth Completion from a Stereo Matching Perspective for Cross-domain Generalization.

[BibT_eX]

[DOI]

CoRR, 2023

The Monocular Depth Estimation Challenge.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, 2023

ScanNeRF: a Scalable Benchmark for Neural Radiance Fields.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Sparsity Agnostic Depth Completion.

[BibT_eX]

[DOI]

Andrea Conti

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Depth Self-Supervision for Single Image Novel View Synthesis.

[BibT_eX]

[DOI]

Giovanni Minelli

Samuele Salti

IROS, 2023

TemporalStereo: Efficient Spatial-Temporal Stereo Matching Network.

[BibT_eX]

[DOI]

Youmin Zhang

IROS, 2023

GasMono: Geometry-Aided Self-Supervised Monocular Depth Estimation for Indoor Scenes.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Learning Depth Estimation for Transparent and Mirror Surfaces.

[BibT_eX]

[DOI]

Alex Costanzino

Theodoros Panagiotakopoulos

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

To Adapt or Not to Adapt? Real-Time Adaptation for Semantic Segmentation.

[BibT_eX]

[DOI]

Marc Botet Colomer

Pier Luigi Dovesi

Joao Frederico Carvalho

Linus Härenstam-Nielsen

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

GO-SLAM: Global Optimization for Consistent 3D Instant Reconstruction.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Active Stereo Without Pattern Projector.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

NeRF-Supervised Deep Stereo.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

The Second Monocular Depth Estimation Challenge.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

NTIRE 2023 Challenge on HR Depth from Images of Specular and Transparent Surfaces.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Contrastive Learning for Depth Prediction.

[BibT_eX]

[DOI]

Rizhao Fan

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

CompletionFormer: Depth Completion with Convolutions and Vision Transformers.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

On-Site Adaptation for Monocular Depth Estimation with a Static Camera.

[BibT_eX]

[DOI]

Proceedings of the 34th British Machine Vision Conference 2023, 2023

Lightweight Self-Supervised Depth Estimation with few-beams LiDAR Data.

[BibT_eX]

[DOI]

Proceedings of the 34th British Machine Vision Conference 2023, 2023

2022

Real-Time Self-Supervised Monocular Depth Estimation Without GPU.

[BibT_eX]

[DOI]

IEEE Trans. Intell. Transp. Syst., 2022

Monitoring Social Distancing With Single Image Depth Estimation.

[BibT_eX]

[DOI]

IEEE Trans. Emerg. Top. Comput. Intell., 2022

Monocular Depth Perception on Microcontrollers for Edge Applications.

[BibT_eX]

[DOI]

IEEE Trans. Circuits Syst. Video Technol., 2022

Continual Adaptation for Deep Stereo.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2022

On the Synergies Between Machine Learning and Binocular Stereo for Depth Estimation From Images: A Survey.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2022

On the Confidence of Stereo Matching in a Deep-Learning Era: A Quantitative Evaluation.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Energy-Quality Scalable Monocular Depth Estimation on Low-Power CPUs.

[BibT_eX]

[DOI]

IEEE Internet Things J., 2022

Semi-Supervised Learning of Monocular Depth Estimation via Consistency Regularization with K-way Disjoint Masking.

[BibT_eX]

[DOI]

CoRR, 2022

Multi-View Guided Multi-View Stereo.

[BibT_eX]

[DOI]

Andrea Conti

Theodoros Panagiotakopoulos

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

Unsupervised confidence for LiDAR depth maps and applications.

[BibT_eX]

[DOI]

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

Meta-confidence estimation for stereo matching.

[BibT_eX]

[DOI]

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

Online Domain Adaptation for Semantic Segmentation in Ever-Changing Conditions.

[BibT_eX]

[DOI]

Pier Luigi Dovesi

Linus Härenstam-Nielsen

Proceedings of the Computer Vision - ECCV 2022, 2022

RED-SEA: Network Solution for Exascale Architectures.

[BibT_eX]

[DOI]

Pier Stanislao Paolucci

Pascale Bernier-Bruna

Giuseppe Piero Brandino

Francesco De Giorgi

Jesús Escudero-Sahuquillo

Iakovos Mavroidis

Yannis Papaefstathiou

Nikolaos Tampouratzis

Vangelis Mageiropoulos

Jennifer Lopez Barillao

Thomas Moschny

Simon Pickartz

Francisco J. Alfaro

Enrique S. Quintana-Ortí

Julio Sahuquillo

Eugenio Stabile

Proceedings of the 25th Euromicro Conference on Digital System Design, 2022

RGB-Multispectral Matching: Dataset, Learning Methodology, Evaluation.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Open Challenges in Deep Stereo: the Booster Dataset.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

A Cascade Dense Connection Fusion Network for Depth Completion.

[BibT_eX]

[DOI]

Proceedings of the 33rd British Machine Vision Conference 2022, 2022

MonoViT: Self-Supervised Monocular Depth Estimation with a Vision Transformer.

[BibT_eX]

[DOI]

Proceedings of the International Conference on 3D Vision, 2022

Cross-Spectral Neural Radiance Fields.

[BibT_eX]

[DOI]

Proceedings of the International Conference on 3D Vision, 2022

2021

Computer Vision for 3D Perception and Applications.

[BibT_eX]

[DOI]

Ludovica Maria Eugenia Mammi

Thomas B. Moeslund

Sensors, 2021

Real-Time Single Image Depth Perception in the Wild with Handheld Devices.

[BibT_eX]

[DOI]

Sensors, 2021

A computer vision approach based on deep learning for the detection of dairy cows in free stall barn.

[BibT_eX]

[DOI]

Comput. Electron. Agric., 2021

Beyond the Baseline: 3D Reconstruction of Tiny Objects With Single Camera Stereo Robot.

[BibT_eX]

[DOI]

Daniele De Gregorio

Gianluca Palli

Luigi Di Stefano

IEEE Access, 2021

Sensor-Guided Optical Flow.

[BibT_eX]

[DOI]

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Learning Optical Flow From Still Images.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Neural Disparity Refinement for Arbitrary Resolution Stereo.

[BibT_eX]

[DOI]

Proceedings of the International Conference on 3D Vision, 2021

2020

Enabling Image-Based Streamflow Monitoring at the Edge.

[BibT_eX]

[DOI]

Remote. Sens., 2020

Unsupervised Domain Adaptation for Depth Prediction from Images.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2020

Learning a confidence measure in the disparity domain from O(1) features.

[BibT_eX]

[DOI]

Comput. Vis. Image Underst., 2020

On the Synergies between Machine Learning and Stereo: a Survey.

[BibT_eX]

[DOI]

CoRR, 2020

Real-Time Semantic Stereo Matching.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Leveraging a weakly adversarial paradigm for joint learning of disparity and confidence estimation.

[BibT_eX]

[DOI]

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Self-adapting Confidence Estimation for Stereo.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2020, 2020

Reversing the Cycle: Self-supervised Deep Stereo Through Enhanced Monocular Distillation.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2020, 2020

Distilled Semantics for Comprehensive Scene Understanding from Videos.

[BibT_eX]

[DOI]

Panteleimon Myriokefalitakis

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

On the Uncertainty of Self-Supervised Monocular Depth Estimation.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Enabling monocular depth perception at the very edge.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Learning End-to-End Scene Flow by Distilling Single Tasks Knowledge.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Matching-space Stereo Networks for Cross-domain Generalization.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on 3D Vision, 2020

2019

Enhancing self-supervised monocular depth estimationwith traditional visual odometry.

[BibT_eX]

[DOI]

Lorenzo Andraghetti

CoRR, 2019

Enabling Energy-Efficient Unsupervised Monocular Depth Estimation on ARMv7-Based Platforms.

[BibT_eX]

[DOI]

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2019

Leveraging Confident Points for Accurate Depth Refinement on Embedded Systems.

[BibT_eX]

[DOI]

Panteleimon Myriokefalitakis

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

Learning Monocular Depth Estimation Infusing Traditional Stereo Knowledge.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Real-Time Self-Adaptive Deep Stereo.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Guided Stereo Matching.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Enhancing Self-Supervised Monocular Depth Estimation with Traditional Visual Odometry.

[BibT_eX]

[DOI]

Lorenzo Andraghetti

Proceedings of the 2019 International Conference on 3D Vision, 2019

2018

Towards Real-Time Unsupervised Monocular Depth Estimation on CPU.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018

Beyond Local Reasoning for Stereo Confidence Estimation with Deep Learning.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2018, 2018

Generative Adversarial Networks for Unsupervised Monocular Depth Prediction.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2018 Workshops, 2018

Geometry Meets Semantics for Semi-supervised Monocular Depth Estimation.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ACCV 2018, 2018

Learning Monocular Depth Estimation with Unsupervised Trinocular Assumptions.

[BibT_eX]

[DOI]

Proceedings of the 2018 International Conference on 3D Vision, 2018

2017

Efficient Confidence Measures for Embedded Stereo.

[BibT_eX]

[DOI]

Proceedings of the Image Analysis and Processing - ICIAP 2017, 2017

Unsupervised Adaptation for Deep Stereo.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Computer Vision, 2017

Quantitative Evaluation of Confidence Measures in a Machine Learning World.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Computer Vision, 2017

Even More Confident Predictions with Deep Machine-Learning.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2017

Learning to Predict Stereo Reliability Enforcing Local Consistency of Confidence Maps.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

Learning confidence measures in the wild.

[BibT_eX]

[DOI]

Proceedings of the British Machine Vision Conference 2017, 2017

2016

A wearable mobility aid for the visually impaired based on embedded 3D vision and deep learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE Symposium on Computers and Communication, 2016

Evaluation of variants of the SGM algorithm aimed at implementation on embedded or reconfigurable devices.

[BibT_eX]

[DOI]

Proceedings of the International Conference on 3D Imaging, 2016

Improving the reliability of 3D people tracking system by means of deep-learning.

[BibT_eX]

[DOI]

Matteo Boschini

Proceedings of the International Conference on 3D Imaging, 2016

Learning from scratch a confidence measure.

[BibT_eX]

[DOI]

Proceedings of the British Machine Vision Conference 2016, 2016

Learning a General-Purpose Confidence Measure Based on O(1) Features and a Smarter Aggregation Strategy for Semi Global Matching.

[BibT_eX]

[DOI]

Proceedings of the Fourth International Conference on 3D Vision, 2016

Deep Stereo Fusion: Combining Multiple Disparity Hypotheses with Deep-Learning.

[BibT_eX]

[DOI]

Proceedings of the Fourth International Conference on 3D Vision, 2016

2015

Crosswalk Recognition Through Point-Cloud Processing and Deep-Learning Suited to a Wearable Mobility Aid for the Visually Impaired.

[BibT_eX]

[DOI]

Luca Nanni

Proceedings of the New Trends in Image Analysis and Processing - ICIAP 2015 Workshops, 2015

A passive RGBD sensor for accurate and real-time depth sensing self-contained into an FPGA.

[BibT_eX]

[DOI]