Fabio Tosi

According to our database1, Fabio Tosi authored at least 41 papers between 2017 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

On csauthors.net:

Bibliography

2023
Booster: a Benchmark for Depth from Images of Specular and Transparent Surfaces.
CoRR, 2023

2022
Real-Time Self-Supervised Monocular Depth Estimation Without GPU.
IEEE Trans. Intell. Transp. Syst., 2022

Monocular Depth Perception on Microcontrollers for Edge Applications.
IEEE Trans. Circuits Syst. Video Technol., 2022

Continual Adaptation for Deep Stereo.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

On the Synergies Between Machine Learning and Binocular Stereo for Depth Estimation From Images: A Survey.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

On the Confidence of Stereo Matching in a Deep-Learning Era: A Quantitative Evaluation.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Energy-Quality Scalable Monocular Depth Estimation on Low-Power CPUs.
IEEE Internet Things J., 2022

The Monocular Depth Estimation Challenge.
CoRR, 2022

Cross-Spectral Neural Radiance Fields.
CoRR, 2022

MonoViT: Self-Supervised Monocular Depth Estimation with a Vision Transformer.
CoRR, 2022

RGB-Multispectral Matching: Dataset, Learning Methodology, Evaluation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Open Challenges in Deep Stereo: the Booster Dataset.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Deep-learning for 3D reconstruction.
PhD thesis, 2021

Real-Time Single Image Depth Perception in the Wild with Handheld Devices.
Sensors, 2021

SMD-Nets: Stereo Mixture Density Networks.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Neural Disparity Refinement for Arbitrary Resolution Stereo.
Proceedings of the International Conference on 3D Vision, 2021

2020
Enabling Image-Based Streamflow Monitoring at the Edge.
Remote. Sens., 2020

Learning a confidence measure in the disparity domain from O(1) features.
Comput. Vis. Image Underst., 2020

On the Synergies between Machine Learning and Stereo: a Survey.
CoRR, 2020

Leveraging a weakly adversarial paradigm for joint learning of disparity and confidence estimation.
Proceedings of the 25th International Conference on Pattern Recognition, 2020

Self-adapting Confidence Estimation for Stereo.
Proceedings of the Computer Vision - ECCV 2020, 2020

Reversing the Cycle: Self-supervised Deep Stereo Through Enhanced Monocular Distillation.
Proceedings of the Computer Vision - ECCV 2020, 2020

Distilled Semantics for Comprehensive Scene Understanding from Videos.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

On the Uncertainty of Self-Supervised Monocular Depth Estimation.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Enabling monocular depth perception at the very edge.
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.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Enabling Energy-Efficient Unsupervised Monocular Depth Estimation on ARMv7-Based Platforms.
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2019

Leveraging Confident Points for Accurate Depth Refinement on Embedded Systems.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

Learning Monocular Depth Estimation Infusing Traditional Stereo Knowledge.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Real-Time Self-Adaptive Deep Stereo.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Guided Stereo Matching.
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.
Remote. Sens., 2018

Towards Real-Time Unsupervised Monocular Depth Estimation on CPU.
Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018

Beyond Local Reasoning for Stereo Confidence Estimation with Deep Learning.
Proceedings of the Computer Vision - ECCV 2018, 2018

Generative Adversarial Networks for Unsupervised Monocular Depth Prediction.
Proceedings of the Computer Vision - ECCV 2018 Workshops, 2018

Geometry Meets Semantics for Semi-supervised Monocular Depth Estimation.
Proceedings of the Computer Vision - ACCV 2018, 2018

Learning Monocular Depth Estimation with Unsupervised Trinocular Assumptions.
Proceedings of the 2018 International Conference on 3D Vision, 2018

2017
Efficient Confidence Measures for Embedded Stereo.
Proceedings of the Image Analysis and Processing - ICIAP 2017, 2017

Quantitative Evaluation of Confidence Measures in a Machine Learning World.
Proceedings of the IEEE International Conference on Computer Vision, 2017

Even More Confident Predictions with Deep Machine-Learning.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2017

Learning confidence measures in the wild.
Proceedings of the British Machine Vision Conference 2017, 2017


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