Poggi, Matteo; Tosi, Fabio; Mattoccia, Stefano, Learning a confidence measure in the disparity domain from O(1) features, «COMPUTER VISION AND IMAGE UNDERSTANDING», 2020, 193, pp. 1 - 8 [articolo]
F. Aleotti, M. Poggi, F. Tosi, S. Mattoccia, Learning end-to-end scene flow by distilling single tasks knowledge, in: Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), Palo Alto, California USA, AAAI Press, «PROCEEDINGS OF THE ... AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE», 2020, 34, pp. 10435 - 10442 (atti di: Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), New York, USA, February 7-12 2020) [Contributo in Atti di convegno]
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) [Contributo in Atti di convegno]
Brevetto 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: 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), IEEE/CVF, 2020, pp. 3224 - 3234 (atti di: Conference on Computer Vision and Pattern Recognition (CVPR), 2020, Seattle, Washington, USA, 13-19 June 2020) [Contributo in Atti di convegno]Open Access
P. L. Dovesi, M. Poggi, L. Andraghetti, M. Martí, H. Kjellström, A. Pieropan, S. Mattoccia, Real-Time Semantic Stereo Matching, in: 2020 IEEE International Conference on Robotics and Automation (ICRA), IEEE, 2020, pp. 10780 - 10787 (atti di: International Conference on Robotics and Automation (ICRA 2020), Paris, France, 31 May 2020 - 31 August 2020) [Contributo in Atti di convegno]Open Access
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, «LECTURE NOTES IN COMPUTER SCIENCE», 2020, 12356, pp. 614 - 632 (atti di: 16th European Conference on Computer Vision (ECCV 2020), Glasgow, UK (Virtual), 23-28 August 2020) [Contributo in Atti di convegno]Open Access
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, «LECTURE NOTES IN COMPUTER SCIENCE», 2020, 12369, pp. 715 - 733 (atti di: 16th European Conference on Computer Vision (ECCV 2020), Glasgow, UK (Virtual), 23-28 August 2020) [Contributo in Atti di convegno]Open Access
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) [capitolo di libro]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 [articolo]Open Access
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) [atti di convegno-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) [Contributo in Atti di convegno]
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) [Contributo in Atti di convegno]
F. Aleotti, F. Tosi, M. Poggi, S. Mattoccia, Generative Adversarial Networks for unsupervised monocular depth prediction, in: Proceedings of 3D Reconstruction in the Wild 2018 (3DRW2018), in conjunction with (ECCV 2018), Springer, 2019, pp. 337 - 354 (atti di: 3D Reconstruction in the Wild 2018 (3DRW2018), ECCV 2018 Workshop, Munich, Germany, September 14, 2018) [Contributo in Atti di convegno]
P. Zama Ramirez, M. Poggi, F. Tosi, S. Mattoccia, L. Di Stefano, Geometry meets semantic for semi-supervised monocular depth estimation, in: Proceedings of the 14th Asian Conference on Computer Vision (ACCV), 2019, pp. 298 - 313 (atti di: 14th Asian Conference on Computer Vision (ACCV), Perth, Australia, December 2-6, 2018) [Contributo in Atti di convegno]
