Name: Alessandro Flaborea
Type: User
Company: Sapienza University of Rome
Bio: PhD in Computer Science @ Sapienza University of Rome. Research focused on Computer Vision and Machine Learning
Twitter: AlessandroFlabo
Location: Rome, Italy
Blog: https://aleflabo.github.io
Alessandro Flaborea's Projects
Analyzing the text of Airbnb property listings and building search engines.
Bayesian analysis on some real data, with the use of MCMC simulations within the OpenBUGS software.
The official PyTorch implementation of the 5th IEEE/CVF CVPR Precognition Workshop paper Best Practices for 2-Body Pose Forecasting.
source code to ICLR'19, 'A Closer Look at Few-shot Classification'
The official PyTorch implementation of the paper Contracting Skeletal Kinematics for Human-Related Video Anomaly Detection, published in the Pattern Recognition Journal.
Jupyter notebook that serves as a tool for identifying duplicate BibTeX items within a reference file.
The official PyTorch implementation of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2024 paper HypΒ²Nav: Hyperbolic Planning and Curiosity for Crowd Navigation.
The official PyTorch implementation of the IEEE/CVF CVPR Visual Anomaly and Novelty Detection (VAND) Workshop paper Are we certain it's anomalous?.
The official PyTorch implementation of the IEEE/CVF International Conference on Computer Vision (ICCV) '23 paper Multimodal Motion Conditioned Diffusion Model for Skeleton-based Video Anomaly Detection.
Issuing badges to credit authors for their work on academic papers
The official PyTorch implementation of the IEEE/CVF Computer Vision and Pattern Recognition (CVPR) '24 paper PREGO: online mistake detection in PRocedural EGOcentric videos.
Scraping the Immobiliare.it site and clustering the information
Partecipation at SUS2019 Hackathon in Milan at the Bocconi University. Awarded as the team which best performed using SAS software and platform.
Statistical Learning project. The team followed all the processes, from the data collection to the data preprocessing and the classification.
The goal of this project is to perform an analysis of the Wikipedia Hyperlink graph and, in particular, to rank the articles within the categories according to some criteria and using NetworkX.
This analysis tries to point out some interresting informations about all the rides made in the first semester of 2018. The work concentrats both in the whole NY city and in the single zones.