Davide Marelli
University of Milano-Bicocca
13 Papers
16 Citations
Davide Marelli is an academic researcher from University of Milano-Bicocca. The author has contributed to research in topics: Computer science & Structure from motion. The author has an hindex of 2, co-authored 7 publications. Previous affiliations of Davide Marelli include University of Milan.
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Papers
Evaluating the Performance of Structure from Motion Pipelines
TL;DR: A comparison of different state-of-the-art SfM pipelines in terms of their ability to reconstruct different scenes is reported and an evaluation procedure is proposed that considers both the reconstruction errors as well as the estimation errors of the camera poses used in the reconstruction.
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A Smart Mirror for Emotion Monitoring in Home Environments
Simone Bianco,Luigi Celona,Gianluigi Ciocca,Davide Marelli,Paolo Napoletano,Stefano Yu,Raimondo Schettini +6 more
TL;DR: In this paper, a general-purpose smart mirror that integrates several functionalities, standard and advanced, to support users in their everyday life is presented, among the advanced functionalities are the capabilities of detecting a person's emotions, the short and long-term monitoring and analysis of the emotions, a double authentication protocol to preserve the privacy, and the integration of Alexa Skills to extend the applications of the smart mirrors.
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Designing an AI-Based Virtual Try-On Web Application
TL;DR: This paper proposes an eyewear virtual try-on experience based on a framework that leverages advanced deep learning-based computer vision techniques, and considers actual glasses and face sizes to provide a realistic fit estimation using a markerless approach.
ENRICH: Multi-purposE dataset for beNchmaRking In Computer vision and pHotogrammetry
Davide Marelli,Luca Morelli,Elisa Mariarosaria Farella,Simone Bianco,Gianluigi Ciocca,Fabio Remondino +5 more
TL;DR: ENRICH as discussed by the authors is a multi-purpose dataset composed of three sub-datasets: ENRICH-Aerial, ENRIC-Square, and ENRIC statue, each exhibiting different characteristics.
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IVL-SYNTHSFM-v2: a synthetic dataset with exact ground truth for the evaluation of 3D reconstruction pipelines
TL;DR: A dataset with 4000 synthetic images portraying five 3D models from different viewpoints under varying lighting conditions to allow evaluation and comparison of different solutions for 3D reconstruction of objects starting from a set of images taken under different realistic acquisition setups.
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