Fabio Tosi

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

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

[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

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

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

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

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

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

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

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

Deep-learning for 3D reconstruction.

[BibT_eX]

[DOI]

PhD thesis, 2021

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

[BibT_eX]

[DOI]

Sensors, 2021

SMD-Nets: Stereo Mixture Density Networks.

[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]

Filippo Aleotti

Proceedings of the International Conference on 3D Vision, 2021

2020

Enabling Image-Based Streamflow Monitoring at the Edge.

[BibT_eX]

[DOI]

Remote. Sens., 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

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]

Filippo Aleotti

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

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]

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

2018

Optical Tracking Velocimetry (OTV): Leveraging Optical Flow and Trajectory-Based Filtering for Surface Streamflow Observations.

[BibT_eX]

[DOI]

Remote. Sens., 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

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]