Journals [14]

2021

  1. Continual Adaptation for Deep Stereo Poggi Matteo, Tonioni Alessio, Tosi Fabio, Mattoccia Stefano, and Di Stefano Luigi IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) [Abs]
  2. On the Synergies between Machine Learning and Binocular Stereo for Depth Estimation from Images: a Survey Poggi Matteo, Tosi Fabio, Batsos Konstantinos, Mordohai Philippos, and Mattoccia Stefano IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) [Abs]
  3. On the confidence of stereo matching in a deep-learning era: a quantitative evaluation Poggi Matteo, Kim Seungryong, Tosi Fabio, Kim Sunok, Aleotti Filippo, Min Dongbo, Sohn Kwanghoon, and Mattoccia Stefano IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) [Abs]
  4. Energy-Quality Scalable Monocular Depth Estimation on Low-Power CPUs Cipolletta Antonio, Peluso Valentino, Calimera Andrea, Poggi Matteo, Tosi Fabio, Aleotti Filippo, and Mattoccia Stefano IEEE IoT Journal (IoT-J) [Abs]
  5. Monocular Depth Perception on Microcontrollers for Edge Applications Peluso Valentino, Cipolletta Antonio, Calimera Andrea, Poggi Matteo, Tosi Fabio, Aleotti Filippo, and Mattoccia Stefano IEEE Transactions on Circuits and Systems for Video Technology (TCSVT) [Abs]
  6. Beyond the Baseline: 3D Reconstructionof Tiny Objects with Single CameraStereo Robot De Gregorio Daniele, Poggi Matteo, Zama Ramirez Pierluigi, Palli Gianluca, Mattoccia Stefano, and Di Stefano Luigi IEEE Access [Abs]
  7. Real-time single image depth perception in the wild with handheld devices Aleotti Filippo, Zaccaroni Giulio, Bartolomei Luca, Poggi Matteo, Tosi Fabio, and Mattoccia Stefano MDPI Sensors [Abs]
  8. On the Deployment of Out-of-the-Box Embedded Devices for Self-Powered River Surface Flow Velocity Monitoring at the Edge Livoroi Arsal-Hanif, Conti Andrea, Foianesi Luca, Tosi Fabio, Aleotti Filippo, Poggi Matteo, Tauro Flavia, Toth Elena, Grimaldi Salvatore, and Mattoccia Stefano Applied Sciences
  9. A computer vision approach based on deep learning for the detection of dairy cows in free stall barn Tassinari Patrizia, Bovo Marco, Benni Stefano, Franzoni Simone, Poggi Matteo, mammi Maria Ludovica Eugenia, Mattoccia Stefano, Di Stefano Luigi, Bonora Filippo, Barbaresi Alberto, Santolini Enrica, and Torreggiani Daniele Computers and Electronics in Agriculture [Abs]

2020

  1. Unsupervised Domain Adaptation for Depth Prediction from Images Tonioni Alessio, Poggi Matteo, Mattoccia Stefano, and Di Stefano Luigi IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) [Abs]
  2. Learning a confidence measure in the disparity domain from O (1) features Poggi Matteo, Tosi Fabio, and Mattoccia Stefano Computer Vision and Image Understanding (CVIU) [Abs]
  3. Confidence Estimation for ToF and Stereo Sensors and its Application to Depth Data Fusion Poggi Matteo, Agresti Gianluca, Tosi Fabio, Zanuttigh Pietro, and Mattoccia Stefano IEEE Sensors Journal [Abs]
  4. Good cues to learn from scratch a confidence measure for passive depth sensors Poggi Matteo, Tosi Fabio, and Mattoccia Stefano IEEE Sensors Journal [Abs]
  5. Enabling image-based streamflow monitoring at the edge Tosi Fabio, Rocca Matteo, Aleotti Filippo, Poggi Matteo, Mattoccia Stefano, Tauro Flavia, Toth Elena, and Grimaldi Salvatore MDPI Remote Sensing [Abs]

Proceedings [37]

2021

  1. Neural Disparity Refinement for Arbitrary Resolution Stereo Aleotti Filippo, Tosi Fabio, Zama Ramirez Pierluigi, Poggi Matteo, Salti Samuele, Di Stefano Luigi, and Mattoccia Stefano In International Conference on 3D Vision (3DV, Oral, Best Paper Honorable Mention) [Abs]
  2. Sensor-Guided Optical Flow Poggi Matteo, Aleotti Filippo, and Mattoccia Stefano In IEEE International Conference on Computer Vision (ICCV) [Abs]
  3. Learning optical flow from still images Aleotti Filippo, Poggi Matteo, and Mattoccia Stefano In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) [Abs]

2020

  1. Matching-space Stereo Networks for Cross-domain Generalization Cai Changjiang, Poggi Matteo, Mattoccia Stefano, and Mordohai Philippos In International Conference on 3D Vision (3DV) [Abs]
  2. Self-adapting confidence estimation for stereo Poggi Matteo, Aleotti Filippo, Tosi Fabio, Zaccaroni Giulio, and Mattoccia Stefano In European Conference on Computer Vision (ECCV) [Abs]
  3. Reversing the cycle: self-supervised deep stereo through enhanced monocular distillation Aleotti Filippo, Tosi Fabio, Zhang Li, Poggi Matteo, and Mattoccia Stefano In European Conference on Computer Vision (ECCV) [Abs]
  4. On the uncertainty of self-supervised monocular depth estimation Poggi Matteo, Aleotti Filippo, Tosi Fabio, and Mattoccia Stefano In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) [Abs]
  5. Distilled semantics for comprehensive scene understanding from videos Tosi Fabio, Aleotti Filippo, Zama Ramirez Pierluigi, Poggi Matteo, Salti Samuele, Di Stefano Luigi, and Mattoccia Stefano In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) [Abs]
  6. Leveraging a weakly adversarial paradigm for joint learning of disparity and confidence estimation Poggi Matteo, Tosi Fabio, Aleotti Filippo, and Mattoccia Stefano In International Conference on Pattern Recognition (ICPR) [Abs]
  7. Enabling monocular depth perception at the very edge Peluso Valentino, Cipolletta Antonio, Calimera Andrea, Poggi Matteo, Tosi Fabio, Aleotti Filippo, and Mattoccia Stefano In IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) [Abs]
  8. Learning End-To-End Scene Flow by Distilling Single Tasks Knowledge Aleotti Filippo, Poggi Matteo, Tosi Fabio, and Mattoccia Stefano In AAAI Conference on Artificial Intelligence (AAAI) [Abs]
  9. Real-time semantic stereo matching Dovesi Pier Luigi, Poggi Matteo, Andraghetti Lorenzo, Martı́ Miquel, Kjellström Hedvig, Pieropan Alessandro, and Mattoccia Stefano In International Conference on Robotics and Automation (ICRA) [Abs]

2019

  1. Guided stereo matching Poggi Matteo, Pallotti Davide, Tosi Fabio, and Mattoccia Stefano In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) [Abs]
  2. Real-time self-adaptive deep stereo Tonioni Alessio, Tosi Fabio, Poggi Matteo, Mattoccia Stefano, and Stefano Luigi Di In IEEE Conference on Computer Vision and Pattern Recognition (CVPR, Oral) [Abs]
  3. Learning monocular depth estimation infusing traditional stereo knowledge Tosi Fabio, Aleotti Filippo, Poggi Matteo, and Mattoccia Stefano In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) [Abs]
  4. Leveraging confident points for accurate depth refinement on embedded systems Tosi Fabio, Poggi Matteo, and Mattoccia Stefano In IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) [Abs]
  5. Enabling energy-efficient unsupervised monocular depth estimation on armv7-based platforms Peluso Valentino, Cipolletta Antonio, Calimera Andrea, Poggi Matteo, Tosi Fabio, and Mattoccia Stefano In Design, Automation & Test in Europe Conference & Exhibition (DATE) [Abs]
  6. Enhancing self-supervised monocular depth estimation with traditional visual odometry Andraghetti Lorenzo, Myriokefalitakis Panteleimon, Dovesi Pier Luigi, Luque Belen, Poggi Matteo, Pieropan Alessandro, and Mattoccia Stefano In International Conference on 3D Vision (3DV) [Abs]

2018

  1. Beyond local reasoning for stereo confidence estimation with deep learning Tosi Fabio, Poggi Matteo, Benincasa Antonio, and Mattoccia Stefano In European Conference on Computer Vision (ECCV) [Abs]
  2. Towards real-time unsupervised monocular depth estimation on cpu Poggi Matteo, Aleotti Filippo, Tosi Fabio, and Mattoccia Stefano In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) [Abs]
  3. Geometry meets semantics for semi-supervised monocular depth estimation Zama Ramirez Pierluigi, Poggi Matteo, Tosi Fabio, Mattoccia Stefano, and Di Stefano Luigi In Asian Conference on Computer Vision (ACCV) [Abs]
  4. Learning monocular depth estimation with unsupervised trinocular assumptions Poggi Matteo, Tosi Fabio, and Mattoccia Stefano In 2018 International Conference on 3D Vision (3DV) [Abs]
  5. Generative adversarial networks for unsupervised monocular depth prediction Aleotti Filippo, Tosi Fabio, Poggi Matteo, and Mattoccia Stefano In European Conference on Computer Vision (ECCVW) [Abs]

2017

  1. Learning to predict stereo reliability enforcing local consistency of confidence maps Poggi Matteo, and Mattoccia Stefano In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) [Abs]
  2. Quantitative evaluation of confidence measures in a machine learning world Poggi Matteo, Tosi Fabio, and Mattoccia Stefano In IEEE International Conference on Computer Vision (ICCV, Spotlight) [Abs]
  3. Unsupervised adaptation for deep stereo Tonioni Alessio, Poggi Matteo, Mattoccia Stefano, and Di Stefano Luigi In IEEE International Conference on Computer Vision (ICCV) [Abs]
  4. Learning confidence measures in the wild. Tosi Fabio, Poggi Matteo, Tonioni Alessio, Di Stefano Luigi, and Mattoccia Stefano In British Machine Vision Conference (BMVC) [Abs]
  5. Even more confident predictions with deep machine-learning Poggi Matteo, Tosi Fabio, and Mattoccia Stefano In IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) [Abs]
  6. Efficient confidence measures for embedded stereo Poggi Matteo, Tosi Fabio, and Mattoccia Stefano In International Conference on Image Analysis and Processing (ICIAP) [Abs]

2016

  1. Learning from scratch a confidence measure. Poggi Matteo, and Mattoccia Stefano In British Machine Vision Conference (BMVC) [Abs]
  2. Learning a general-purpose confidence measure based on o (1) features and a smarter aggregation strategy for semi global matching Poggi Matteo, and Mattoccia Stefano In International Conference on 3D Vision (3DV, Oral) [Abs]
  3. Deep stereo fusion: combining multiple disparity hypotheses with deep-learning Poggi Matteo, and Mattoccia Stefano In International Conference on 3D Vision (3DV) [Abs]
  4. A wearable mobility aid for the visually impaired based on embedded 3d vision and deep learning Poggi Matteo, and Mattoccia Stefano In 2016 IEEE Symposium on Computers and Communication (ISCC) [Abs]
  5. Evaluation of variants of the sgm algorithm aimed at implementation on embedded or reconfigurable devices Poggi Matteo, and Mattoccia Stefano In 2016 International Conference on 3D Imaging (IC3D) [Abs]
  6. Improving the reliability of 3D people tracking system by means of deep-learning Boschini Matteo, Poggi Matteo, and Mattoccia Stefano In 2016 International Conference on 3D Imaging (IC3D) [Abs]

2015

  1. Crosswalk recognition through point-cloud processing and deep-learning suited to a wearable mobility aid for the visually impaired Poggi Matteo, Nanni Luca, and Mattoccia Stefano In International Conference on Image Analysis and Processing (ICIAP) [Abs]
  2. A passive RGBD sensor for accurate and real-time depth sensing self-contained into an FPGA Mattoccia Stefano, and Poggi Matteo In International Conference on Distributed Smart Cameras (ICDSC) [Abs]