Scholar
Sergio Izquierdo
Google Scholar ID: 5rAK6moAAAAJ
PhD candidate at University of Zaragoza
Deep Learning
Computer Vision
Computer Science
Artificial Intelligence
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Citations & Impact
All-time
Citations
208
H-index
5
i10-index
4
Publications
9
Co-authors
0
Contact
Email
izquierdo@unizar.es
CV
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GitHub
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Publications
2 items
MVSAnywhere: Zero-Shot Multi-View Stereo
2025
Cited
1
Single-Shot Metric Depth from Focused Plenoptic Cameras
arXiv.org · 2024
Cited
0
Resume (English only)
Academic Achievements
Paper: 'MVSAnywhere: Zero-Shot Multi-View Stereo', CVPR 2025
Paper: 'Close, But Not There: Boosting Geographic Distance Sensitivity in Visual Place Recognition', ECCV 2024
Paper: 'Optimal Transport Aggregation for Visual Place Recognition', CVPR 2024
Paper: 'SfM-TTR: Using Structure from Motion for Test-Time Refinement of Single-View Depth Networks', CVPR 2023
Paper: 'Conditional Servoing for Multi-Step Tasks', IROS 2022
Paper: 'Bag of Baselines for Multi-objective Joint Neural Architecture Search and Hyperparameter Optimization', ICML 2021 AutoML Workshop
Paper: 'Semi-Supervised Disparity Estimation with Deep Feature Reconstruction', CVPR Workshops 2021
Created and maintains the open-source library CppFlow for running TensorFlow models from C++, widely used by developers and companies
Awarded the FPU PhD Scholarship by the Spanish Ministry of Education (2021–present)
Recipient of the Deutschlandstipendium national scholarship (2020–2021)
Ranked among top Computer Science graduates in Spain by SEDEA in 2020
Received a Collaboration Scholarship from the Spanish Ministry of Education in 2018 for a research project on Deep Learning + SLAM
Background
PhD student in Computer Vision at the University of Zaragoza, Spain
Research interests: Deep Learning, Self-Supervised Learning, Computer Vision
Focuses on 3D reconstruction and computer vision by combining deep learning priors with geometric cues
Technical skills: Python, PyTorch, TensorFlow, OpenCV, C++
Languages: Spanish (Native), English (C1 CAE)
Co-authors
0 total
Co-authors: 0 (list not available)
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