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Stefano Mattoccia

Stefano Mattoccia

D-Index & Metrics

Computer Science

D-Index
43
Citations
7340
World Ranking
8019
National Ranking
215

Overview

Stefano Mattoccia is affiliated with the University of Bologna in Italy. Their research primarily focuses on fields related to Computer Science and Engineering, with a particular emphasis on Computer Vision and Pattern Recognition. They have also contributed to Media Technology and Aerospace Engineering, demonstrating a multidisciplinary approach to their work.

The scientist's research topics include Advanced Vision and Imaging, Optical Measurement and Interference Techniques, Image Processing Techniques and Applications, Advanced Image Processing Techniques, Robotics and Sensor-Based Localization, Image Enhancement Techniques, and Advanced Optical Sensing Technologies.

Stefano Mattoccia has published extensively, with recent papers covering diverse aspects of computer vision and image-based sensing technologies. Notable recent publications include:

  • "On the Synergies between Machine Learning and Binocular Stereo for Depth Estimation from Images: a Survey" (2021) published in IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "A computer vision approach based on deep learning for the detection of dairy cows in free stall barn" (2021) published in Computers and Electronics in Agriculture
  • "Semantisk stereomatchning i realtid" (2020) published in Publications (Konstfack University of Arts, Crafts, and Design)
  • "Real-Time Single Image Depth Perception in the Wild with Handheld Devices" (2020) published in MDPI (MDPI AG)
  • "Enabling Image-Based Streamflow Monitoring at the Edge" (2020) published in Remote Sensing

Their frequent coauthors include Matteo Poggi, Fabio Tosi, Filippo Aleotti, Luigi Di Stefano, and Pierluigi Zama Ramirez. Collaboration with these researchers reflects ongoing teamwork in advancing topics within the computer vision and imaging fields.

Stefano Mattoccia has contributed significantly to several publication venues, most frequently publishing in:

  • arXiv (Cornell University)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • International Journal of Computer Vision
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Computer Vision and Image Understanding

Best Publications

  • A fast area-based stereo matching algorithm

    Luigi Di Stefano;Massimiliano Marchionni;Stefano Mattoccia

  • Segmentation-based adaptive support for accurate stereo correspondence

    Federico Tombari;Stefano Mattoccia;Luigi Di Stefano

  • ZNCC-based template matching using bounded partial correlation

    Luigi Di Stefano;Stefano Mattoccia;Federico Tombari

  • Classification and evaluation of cost aggregation methods for stereo correspondence

    F. Tombari;S. Mattoccia;L. Di Stefano;E. Addimanda

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

    Unknown

  • Real-Time Self-Adaptive Deep Stereo

    Alessio Tonioni;Fabio Tosi;Matteo Poggi;Stefano Mattoccia

  • Learning Monocular Depth Estimation Infusing Traditional Stereo Knowledge

    Fabio Tosi;Filippo Aleotti;Matteo Poggi;Stefano Mattoccia

  • On the Uncertainty of Self-Supervised Monocular Depth Estimation

    Matteo Poggi;Filippo Aleotti;Fabio Tosi;Stefano Mattoccia

  • Fast template matching using bounded partial correlation

    Luigi Di Stefano;Stefano Mattoccia

  • Learning Monocular Depth Estimation with Unsupervised Trinocular Assumptions

    Matteo Poggi;Fabio Tosi;Stefano Mattoccia

  • Accurate and efficient cost aggregation strategy for stereo correspondence based on approximated joint bilateral filtering

    Stefano Mattoccia;Simone Giardino;Andrea Gambini

  • Towards Real-Time Unsupervised Monocular Depth Estimation on CPU

    Matteo Poggi;Filippo Aleotti;Fabio Tosi;Stefano Mattoccia

  • Performance Evaluation of Full Search Equivalent Pattern Matching Algorithms

    Wanli Ouyang;F. Tombari;S. Mattoccia;L. Di Stefano

  • Linear stereo matching

    Leonardo De-Maeztu;Stefano Mattoccia;Arantxa Villanueva;Rafael Cabeza

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

    Matteo Poggi;Stefano Mattoccia

  • CompletionFormer: Depth Completion with Convolutions and Vision Transformers

    Unknown

  • Geometry Meets Semantics for Semi-supervised Monocular Depth Estimation

    Pierluigi Zama Ramirez;Matteo Poggi;Fabio Tosi;Stefano Mattoccia

  • On the Synergies between Machine Learning and Binocular Stereo for Depth Estimation from Images: a Survey.

    Matteo Poggi;Fabio Tosi;Konstantinos Batsos;Philippos Mordohai

  • Fast Full-Search Equivalent Template Matching by Enhanced Bounded Correlation

    S. Mattoccia;F. Tombari;L. Di Stefano

  • Unsupervised Adaptation for Deep Stereo

    Alessio Tonioni;Matteo Poggi;Stefano Mattoccia;Luigi Di Stefano

  • An efficient algorithm for exhaustive template matching based on normalized cross correlation

    L. Di Stefano;S. Mattoccia;M. Mola

  • Learning from scratch a confidence measure.

    Matteo Poggi;Stefano Mattoccia

  • Generative Adversarial Networks for Unsupervised Monocular Depth Prediction

    Filippo Aleotti;Fabio Tosi;Matteo Poggi;Stefano Mattoccia

Frequent Co-Authors

Luigi Di Stefano
Luigi Di Stefano University of Bologna
Federico Tombari
Federico Tombari Technical University of Munich
Salvatore Grimaldi
Salvatore Grimaldi Tuscia University
Kwanghoon Sohn
Kwanghoon Sohn Yonsei University
Dongbo Min
Dongbo Min Ewha Womans University
Gianluca Palli
Gianluca Palli University of Bologna
Claudio Melchiorri
Claudio Melchiorri University of Bologna
Ghassan AlRegib
Ghassan AlRegib Georgia Institute of Technology
Wanli Ouyang
Wanli Ouyang Shanghai AI Lab

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