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Name: Nicola Dall'Asen

Type: User

Bio: AI PhD student @ University of Pisa and Trento, Italy. Generative models and nerdy stuff.

Hi there 👋

I'm an Italian developer with a strong interest in Statistics, Deep Learning and Computer Vision, as I'm sure these tools can be used to foster human progress.

🌱 I’m currently pursuing my PhD in Artificial Intelligence in a joint program between University of Pisa and University of Trento, Italy.

Nicola Dall'Asen's Projects

adaptivewingloss

[ICCV 2019] Adaptive Wing Loss for Robust Face Alignment via Heatmap Regression - Official Implementation

al-folio

A beautiful, simple, clean, and responsive Jekyll theme for academics

anonygan

Official PyTorch implementation of the paper "Graph-based Generative Face Anonymisation with Pose Preservation" in ICIAP 2021

arxivdigest

ArXiv Digest and Personalized Recommendations using Large Language Models

auto-base16-theme

Automatically generate a base16 color set for syntax highlighting based on the colors in an image

chatpgt-telegram

Run your own GPTChat Telegram bot, with a single command!

cheatsheet-translation

Translation of VIP cheatsheets for Machine Learning Deep Learning, and Artificial Intelligence

covid-19-bl

Evoluzione del coronavirus nella provincia di Belluno, aggiornata ogni giorno con dati ufficiali presi da Azienda Zero.

deepseek-vl

DeepSeek-VL: Towards Real-World Vision-Language Understanding

deno-api-mongo

A scaffold application to provide a set of API in Deno to interact with a MongoDB database.

denoising-diffusion-gan

Tackling the Generative Learning Trilemma with Denoising Diffusion GANs https://arxiv.org/abs/2112.07804

dl-visualization

This is the source code for the animations in the series "Visualizing Deep Learning"

dlwpt-code

Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.

erdos-graphwalker

Calculate coauthorship distance using data extracted from Google Scholar

express-knex-objection

A simple API system on a pg database, using knex and objection to simplify connection and management

faceshifter

Unofficial PyTorch Implementation for FaceShifter (https://arxiv.org/abs/1912.13457)

This project provides an official implementation of our recent work on real-time multi-object tracking in videos. The previous works conduct object detection and tracking with two separate models so they are very slow. In contrast, we propose a one-stage solution which does detection and tracking with a single network by elegantly solving the alignment problem. The resulting approach achieves groundbreaking results in terms of both accuracy and speed: (1) it ranks first among all the trackers on the MOT challenges; (2) it is significantly faster than the previous state-of-the-arts. In addition, it scales gracefully to handle a large number of objects.

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Hi there 👋

Nicola Dall'Asen's Projects

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