Thesis Hall of Fame

Here you can find some particularly worthy theses, some of which have been then evolved into papers published at Workshops, Conferences and Journals.

Our students A. Marelli, F. Azzoni, and M. Farina proudly presenting their work during a poster session at international conferences.
  • Francesco Azzoni, Deep Monocular Autocalibration of Radially Symmetric Wide-Angle Cameras.
    The work has been published and presented at ECCV 2024.
  • Andrea Marelli, Temporal consistent CAMs for weakly supervised video segmentation in Waste Sorting
    The work has been published and presented at the Industrial Vision Workshop hosted at ECCV 2024.
  • Carlo Sgaravatti, A Multimodal Hybrid Late-Cascade Fusion Network for Enhanced 3D Object Detection
    The work has been published and presented at the Industrial Vision Workshop hosted at ECCV 2024.
  • Olmo Michelangelo Notarianni, Change Detection in Multivariate data streams: Online Analysis with Kernel-QuantTree
    The work has been published and presented at the Advanced Analytics and Learning on Temporal Data Workshop at ECML 2024
  • Fiore Amarù, Michele Alziati, Ensemble clustering via synchronized relabelling.
    The work has been published at Pattern Recognition Letters, August 2024
  • Matteo Farina, Quantum Multi-Model Fitting.
    The work has been published and presented as an highlights at CVPR 2023.
  • Andrea Porfiri Dal Cin, Synchronization of Group-labelled Multi-graphs.
    The work has been published and presented at ICCV 2022.

Other theses to have a look at:

  • Romeo, Forcing latent space Disentanglement for enhanced model Explainability. summary, ppt
  • Rios,Geometric Supervision for Efficient Reconstruction and Pose Refinement in Neural Radiance Fields summary
  • Mariusz,SE3D: A Framework for Saliency Method Evaluation in 3D Medi- cal Imaging. summary, ppt
  • Musiari, Unsupervised Illegal Landfills Detection using Land Cover specic Autoencoders. summary, ppt
  • Puddu, Enhanced Graph Reconstruction using Graph Neural Networks. summary, ppt
  • Innocenti, Diffusion Models for Image Motion Blur Removal. summary, ppt
  • Basla, Generative Data Augmentation for Instance Segmentation in Fluorescence Microscopy Images. summary.
  • Rizzo, Enhancing QuantTree using kernel functions. summary, ppt
  • Gusmeroli, summary, ppt
  • Peretti, Enhancing CNN for Image Denoising by Promoting Non-Local Self-Similarity. summary
  • Diecidue, Detection of Critical Faults in Deep Neural Networks via auxiliary models. ppt
  • Leveni, Non-planar Object Detection and Identification by Features Matching and Triangulation Growth. ppt