Computer Vision and Multimedia Lab

About Us

The Computer Vision & Multimedia Laboratory (CVML) has been active in the Department of Electrical, Computer and Biomedical Engineering of the University of Pavia since the early 70s. The group's initial research activities concentrated on image enhancement and restoration techniques, with a particular focus on medical imagery. Subsequently, the group's main efforts have been devoted to more advanced image processing functions, involving scene segmentation and shape characterization; a broad background has been acquired on low-level and intermediate-level vision tasks involving grey-level statistics and structural descriptions. Since the early 80s a new stream of research has been actively followed in the field of parallel architectures for vision and image processing. The group has meanwhile developed skills in high-level image processing domains, such as the management of knowledge description and learning capabilities for vision tasks.

Research, Projects and Awards

New research areas have been activated on Computer Vision and Pattern Recognition, Deep Learning applications, Eye Tracking for human-computer interaction and biometrics, Digital Humanities and 3D modeling for dissemination and accessibility of cultural heritage, Social Media Analysis.
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PhD projects

in progress and completed
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Thesis projects / Proposte di tesi

Developing and testing algorithms, eye tracking applications, cloud computing, 3D modeling, gesture interaction, user behavior detection, ... for a full list
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Awards

Best PhD thesis, best paper, best student recognition, top 40 under 40, ... for a full list
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News

• 23-27 May 2022 PART2021 (PArts can woRth like The whole) first international workshop, held in conjunction with ICIAP2021,
  both virtual and in presence, in Lecce (Italy).
  Two challenges are linked to PART2021: CLEOPATRA and M2FRED
• Offerte di lavoro e avvisi in BACHECA Please find two calls for internship at the University of Paris Saclay: CNN-Based Fresco Reconstruction and Generative Art for Image Reconstruction

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