Foto del docente

Pierluigi Zama Ramirez

Junior assistant professor (fixed-term)

Department of Computer Science and Engineering

Academic discipline: ING-INF/05 Information Processing Systems

Publications

Adriano Cardace, Riccardo Spezialetti, Pierluigi Zama Ramirez, Samuele Salti, Luigi Di Stefano, Self-Distillation for Unsupervised 3D Domain Adaptation, in: 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), New York, IEEE, 2023, pp. 4166 - 4177 (atti di: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Waikoloa, Hawai, 3-7 Jan. 2023) [Contribution to conference proceedings]Open Access

Matteo Poggi, Pierluigi Zama Ramirez, Fabio Tosi, Samuele Salti, Stefano Mattoccia, Luigi Di Stefano, Cross-Spectral Neural Radiance Fields, in: Proceedings of the International Conference on 3D Vision (3DV), 2022, pp. 1 - 8 (atti di: International Conference on 3D Vision (3DV), Praga, Repubblica Ceca, 12 settembre 2022) [Contribution to conference proceedings]

Ramirez, Pierluigi Zama; Tosi, Fabio; Poggi, Matteo; Salti, Samuele; Mattoccia, Stefano; Di Stefano, Luigi, Open Challenges in Deep Stereo: the Booster Dataset, in: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), IEEE, 2022, pp. 21136 - 21146 (atti di: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2022), New Orleans, LA, USA, 18-24 June 2022) [Contribution to conference proceedings]Open Access

Adriano Cardace, Luca De Luigi, Pierluigi Zama Ramirez, Samuele Salti, Luigi Di Stefano;, Plugging Self-Supervised Monocular Depth Into Unsupervised Domain Adaptation for Semantic Segmentation, in: 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), IEEE, 2022, pp. 1999 - 2009 (atti di: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Waikoloa, Hawai, 3-8 Jan. 2022) [Contribution to conference proceedings]Open Access

Tosi, Fabio; Ramirez, Pierluigi Zama; Poggi, Matteo; Salti, Samuele; Mattoccia, Stefano; Di Stefano, Luigi, RGB-Multispectral Matching: Dataset, Learning Methodology, Evaluation, in: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022, pp. 15937 - 15947 (atti di: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), New Orleans, LA, USA, 18-24 June 2022) [Contribution to conference proceedings]Open Access

Adriano Cardace; Pierluigi Zama Ramirez; Samuele Salti; Luigi Di Stefano, Shallow Features Guide Unsupervised Domain Adaptation for Semantic Segmentation at Class Boundaries, in: 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), IEEE, 2022, pp. 2010 - 2020 (atti di: 22nd IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2022, Waikoloa, Hawai, 4-8 Jan. 2022) [Contribution to conference proceedings]Open Access

De Gregorio D.; Poggi M.; Zama Ramirez P.; Palli G.; Mattoccia S.; Di Stefano L., Beyond the Baseline: 3D Reconstruction of Tiny Objects with Single Camera Stereo Robot, «IEEE ACCESS», 2021, 9, pp. 119755 - 119765 [Scientific article]Open Access

Filippo Aleotti, Fabio Tosi, Pierluigi Zama Ramirez, Matteo Poggi, Samuele Salti, Stefano Mattoccia, Luigi Di Stefano, Neural Disparity Refinement for Arbitrary Resolution Stereo, in: 2021 International Conference on 3D Vision (3DV), IEEE, 2021, pp. 207 - 217 (atti di: 2021 International Conference on 3D Vision (3DV), London, United Kingdom, 1-3 Dec. 2021) [Contribution to conference proceedings]

Adriano Cardace; Riccardo Spezialetti ; Pierluigi Zama Ramirez; Samuele Salti; Luigi Di Stefano, RefRec: Pseudo-labels Refinement via Shape Reconstruction for Unsupervised 3D Domain Adaptation, in: 2021 International Conference on 3D Vision (3DV), IEEE, 2021, pp. 331 - 341 (atti di: 9th International Conference on 3D Vision (3DV), London, United Kingdom, Dec. 1 2021 to Dec. 3 2021) [Contribution to conference proceedings]Open Access

F. Tosi, F. Aleotti, P. Zama Ramirez, M. Poggi, S. Salti, L. Di Stefano, S. Mattoccia, Distilled semantics for comprehensive scene understanding from videos, in: 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), IEEE/CVF, 2020, pp. 4653 - 4664 (atti di: Conference on Computer Vision and Pattern Recognition (CVPR), 2020, Washington, USA, June 16-18, 2020, Seattle) [Contribution to conference proceedings]Open Access

Pierluigi Zama Ramirez; Claudio Paternesi; Luigi Di Lella; Daniele De Gregorio; Luigi Di Stefano, Shooting Labels: 3D Semantic Labeling by Virtual Reality, in: 2020 IEEE International Conference on Artificial Intelligence and Virtual Reality, AIVR 2020, Institute of Electrical and Electronics Engineers Inc., 2020, pp. 99 - 106 (atti di: 3rd IEEE International Conference on Artificial Intelligence and Virtual Reality, AIVR 2020, Utrecht, Netherlands, 14-18 December 2020) [Contribution to conference proceedings]Open Access

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) [Contribution to conference proceedings]

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, 2019, pp. 8109 - 8118 (atti di: 2019 IEEE/CVF International Conference on Computer Vision (ICCV), Seoul, South Korea, 27 Oct.-2 Nov. 2019) [Contribution to conference proceedings]

Pierluigi Zama, Alessio Tonioni, Luigi Di Stefano, Exploiting Semantics in Adversarial Training for Image-Level Domain Adaptation, in: Proceedings of the Third IEEE International Conference on Image Processing, Applications and Systems (IPAS 2018), 2018, pp. 49 - 54 (atti di: International Conference on Image Processing, Applications and Systems (IPAS 2018), Sophia Antipholis, France, 12/12/2018-14/12/2018) [Contribution to conference proceedings]

Latest news

At the moment no news are available.