Foto del docente

Luigi Di Stefano

Professore ordinario

Dipartimento di Informatica - Scienza e Ingegneria

Settore scientifico disciplinare: IINF-05/A Sistemi di elaborazione delle informazioni

Pubblicazioni

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

Spezialetti, Riccardo; Salti, Samuele; Di Stefano, Luigi; Tombari, Federico, 3D Local Descriptors—from Handcrafted to Learned, in: 3D Imaging, Analysis and Applications, Cham, Springer, 2020, pp. 319 - 352 [capitolo di libro]Open Access

Marcon Marlon; Spezialetti Riccardo; Salti Samuele; Silva Luciano; Di Stefano Luigi, Boosting Object Recognition in Point Clouds by Saliency Detection, in: New Trends in Image Analysis and Processing – ICIAP 2019, Springer Verlag, «LECTURE NOTES IN COMPUTER SCIENCE», 2019, 11808, pp. 321 - 331 (atti di: Industrial session held at the 20th International Conference on Image Analysis and Processing, ICIAP 2019, Italia, 13/09/2019) [Contributo in Atti di convegno]

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]

Tonioni A.; Di Stefano L., Domain invariant hierarchical embedding for grocery products recognition, «COMPUTER VISION AND IMAGE UNDERSTANDING», 2019, 182, pp. 81 - 92 [articolo]

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]

S. Melzi; R. Spezialetti; F. Tombari; M. M. Bronstein; L. Di Stefano; E. Rodolà, Gframes: Gradient-based local reference frame for 3D shape matching, in: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, IEEE Computer Society, «IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION», 2019, 2019, pp. 4624 - 4633 (atti di: 32nd IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2019, usa, 2019) [Contributo in Atti di convegno]

Ramirez, Pierluigi Zama; Tonioni, Alessio; Salti, Samuele; Stefano, Luigi Di, Learning Across Tasks and Domains, in: 2019 IEEE/CVF International Conference on Computer Vision (ICCV), IEEE, «PROCEEDINGS IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION», 2019, pp. 8109 - 8118 (atti di: 2019 IEEE/CVF International Conference on Computer Vision (ICCV), Seoul, South Korea, 27 Oct.-2 Nov. 2019) [Contributo in Atti di convegno]

Spezialetti, Riccardo; Salti, Samuele; Stefano, Luigi Di, Learning an Effective Equivariant 3D Descriptor Without Supervision, in: 2019 IEEE/CVF International Conference on Computer Vision (ICCV), «PROCEEDINGS IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION», 2019, pp. 6400 - 6409 (atti di: 2019 IEEE/CVF International Conference on Computer Vision (ICCV), Seoul, South Korea, 27 Oct.-2 Nov. 2019) [Contributo in Atti di convegno]

Tonioni A.; Rahnama O.; Joy T.; DI Stefano L.; Ajanthan T.; Torr P.H.S., Learning to adapt for stereo, in: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, IEEE Computer Society, «PROCEEDINGS - IEEE COMPUTER SOCIETY CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION», 2019, 2019-, pp. 9653 - 9662 (atti di: 32nd IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2019, usa, 2019) [Contributo in Atti di convegno]

Brevetto n. 102019000022707, Metodo per determinare la profondità da immagini mediante apprendimento auto-adattivo di una rete neurale e relativo sistema.

Spezialetti Riccardo; Salti Samuele; Di Stefano Luigi, Performance evaluation of learned 3D features, in: Image Analysis and Processing – ICIAP 2019, Springer Verlag, «LECTURE NOTES IN COMPUTER SCIENCE», 2019, 11751, pp. 519 - 531 (atti di: 20th International Conference on Image Analysis and Processing, ICIAP 2019, Trento, Italia, 2019) [Contributo in Atti di convegno]

Rahnama O.; Cavallari T.; Golodetz S.; Tonioni A.; Joy T.; Di Stefano L.; Walker S.; Torr P.H.S., Real-Time Highly Accurate Dense Depth on a Power Budget Using an FPGA-CPU Hybrid SoC, «IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS. II, EXPRESS BRIEFS», 2019, 66, Article number: 8681073, pp. 773 - 777 [articolo]Open Access

A. Tonioni, F. Tosi , M. Poggi, S. Mattoccia, L. Di Stefano, Real-time self-adaptive deep stereo, in: 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), New York, IEEE/CVF, 2019, pp. 195 - 204 (atti di: IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2019), Long Beach, CA, USA, June 16-20 2019) [Contributo in Atti di convegno]Open Access

Tonioni, Alessio, Eugenio Serra, Luigi Di Stefano, A deep learning pipeline for product recognition on store shelves, in: Proceedings of the Third IEEE International Conference on Image Processing, Applications and Systems (IPAS 2018), 2018, pp. 25 - 31 (atti di: International Conference on Image Processing, Applications and Systems (IPAS 2018), Sophia Antipholis, France, 12/12/2018-14/12/2018) [Contributo in Atti di convegno]