Foto del docente

Stefano Mattoccia

Associate Professor

Department of Computer Science and Engineering

Academic discipline: ING-INF/05 Information Processing Systems

Publications

Changjiang Cai, Matteo Poggi, Stefano Mattoccia, Philippos Mordohai, Matching-space Stereo Networks for Cross-domain Generalization, in: Proceedings of the 8th International Virtual Conference on 3D Vision (3DV 2020), 2020, pp. 364 - 373 (atti di: 8th International Virtual Conference on 3D Vision (3DV 2020), Online conference due to COVID-19, November 25-28 2020) [Contribution to conference proceedings]

Patent n. 102020000016054, Method for determining the confidence of a disparity map through a self-adaptive learning of a neural network, and sensor system thereof.

M. Poggi, F. Aleotti, F. Tosi, S. Mattoccia, On the Uncertainty of Self-Supervised Monocular Depth Estimation, in: The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020, IEEE/CVF, 2020, pp. 3227 - 3237 (atti di: The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020, Seattle, Washington, USA, June 16-18, 2020) [Contribution to conference proceedings]

P. L. Dovesi, M. Poggi, L. Andraghetti, M. Martí, H. Kjellström, A. Pieropan, S. Mattoccia, Real-Time Semantic Stereo Matching, in: International Conference on Robotics and Automation (ICRA 2020), IEEE, 2020, pp. 1 - 8 (atti di: International Conference on Robotics and Automation (ICRA 2020), Paris, France, May 31-June 4, 2020) [Contribution to conference proceedings]

Aleotti, Filippo; Zaccaroni, Giulio; Bartolomei, Luca; Poggi, Matteo; Tosi, Fabio; Mattoccia, Stefano, Real-Time Single Image Depth Perception in the Wild with Handheld Devices, «SENSORS», 2020, 21, pp. 1 - 17 [Scientific article]

F. Aleotti, F. Tosi, L. Zhang, M. Poggi, S. Mattoccia,, Reversing the cycle: self-supervised deep stereo through enhanced monocular distillation, in: 16th European Conference on Computer Vision (ECCV 2020), Heidelberg, Springer, 2020, 12356, pp. 614 - 632 (atti di: 16th European Conference on Computer Vision (ECCV 2020), Glasgow, UK (Virtual), 23-28 August 2020) [Contribution to conference proceedings]

M. Poggi, F. Aleotti, F. Tosi, Giulio Zaccaroni, S. Mattoccia, Self-adapting confidence estimation for stereo, in: 16th European Conference on Computer Vision (ECCV 2020), Heidelberg, Springer, 2020, 12369, pp. 715 - 733 (atti di: 16th European Conference on Computer Vision (ECCV 2020), Glasgow, UK (Virtual), 23-28 August 2020) [Contribution to conference proceedings]

Arcidiacono C.; Barbari M.; Benni S.; Carfagna E.; Cascone G.; Conti L.; di Stefano L.; Guarino M.; Leso L.; Lovarelli D.; Mancino M.; Mattoccia S.; Minozzi G.; Porto S.M.C.; Provolo G.; Rossi G.; Sandrucci A.; Tamburini A.; Tassinari P.; Tomasello N.; Torreggiani D.; Valenti F., Smart Dairy Farming: Innovative Solutions to Improve Herd Productivity, in: Innovative Biosystems Engineering for Sustainable Agriculture, Forestry and Food Production, Cham, Springer, 2020, pp. 265 - 270 (LECTURE NOTES IN CIVIL ENGINEERING) [Chapter or essay]Open Access

Tonioni, Alessio; Poggi, Matteo; Mattoccia, Stefano; Di Stefano, Luigi, Unsupervised Domain Adaptation for Depth Prediction from Images, «IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE», 2020, 42, pp. 2396 - 2409 [Scientific article]

Stefano Benni, Filippo Bonora, Luigi Di Stefano, Stefano Mattoccia, Matteo Poggi, Patrizia Tassinari, Daniele Torreggiani, COMPUTER VISION IDENTIFICATION AND POSITION DETECTION OF FRIESIAN COWS, in: Biosystem Engineering for sustainable agriculture, forestry and food production Conference Proceedings Book, 2019, pp. 211 - 211 (atti di: Biosystem Engineering for sustainable agriculture, forestry and food production, Matera (Italy), 12-13 September 2019) [Abstract]

Peluso V.; Cipolletta A.; Calimera A.; Poggi M.; Tosi F.; Mattoccia S., Enabling Energy-Efficient Unsupervised Monocular Depth Estimation on ARMv7-Based Platforms, in: Proceedings of the 2019 Design, Automation and Test in Europe Conference and Exhibition, DATE 2019, Institute of Electrical and Electronics Engineers Inc., 2019, pp. 1703 - 1708 (atti di: 22nd Design, Automation and Test in Europe Conference and Exhibition, DATE 2019, Firenze Fiera, ita, 2019) [Contribution to conference proceedings]

Andraghetti L.; Myriokefalitakis P.; Dovesi P.L.; Luque B.; Poggi M.; Pieropan A.; Mattoccia S., Enhancing Self-Supervised Monocular Depth Estimation with Traditional Visual Odometry, in: Proceedings - 2019 International Conference on 3D Vision, 3DV 2019, Institute of Electrical and Electronics Engineers Inc., 2019, pp. 424 - 433 (atti di: 7th International Conference on 3D Vision, 3DV 2019, Quebec City, Canada, September 16-19 2019) [Contribution to conference proceedings]

M. Poggi, D. Pallotti, F. Tosi, S. Mattoccia, Guided stereo matching, in: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019, IEEE/CVF, 2019, pp. 979 - 988 (atti di: IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2019), Long Beach, CA, USA, June 16-20 2019) [Contribution to conference proceedings]

F. Tosi, F. Aleotti, M. Poggi, S. Mattoccia, Learning monocular depth estimation infusing traditional stereo knowledge, in: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019, IEEE/CVF, 2019, pp. 9799 - 9809 (atti di: IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2019), Long Beach, CA, USA, June 16-20 2019) [Contribution to conference proceedings]

F. Tosi , M. Poggi, S. Mattoccia, Leveraging confident points for accurate depth refinement on embedded systems, in: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2019, Computer Vision Foundation, 2019, pp. 1 - 10 (atti di: 15th IEEE Embedded Vision Workshop (EVW 2019) held in conjunction with CVPR 2019, Long Beach (USA), June 16 2019) [Contribution to conference proceedings]

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