Biomechanics Capture
Deep learning based biomechanics capture
Deep learning based biomechanics capture
Projects developed during the unicredit internship.
Gesture recognition using machine learning for wearable motion controller
Human activity and emotion recognition fromRGB videos using deep learning
The robot is developed during the Robotics and design course at Politecnico Di Milano.
Multiplayer computer game developed using Unity. The game was developed for game design class of POLIMI.
Online book store developed during web development class of POLIMI.
Published in EuroGraphics 2022, 2022
Recommended citation: Arnab Dey, Andrew I. Comport. RGB-D Neural Radiance Fields: Local Sampling for Faster Training https://diglib.eg.org/handle/10.2312/egp20221001
Published in WSCG 2022, 2022
computer vision, Neural Radiance fields
Recommended citation: Dey, A. and Ahmine, Y. and Comport, A.I., Mip-NeRF RGB-D: Depth Assisted Fast Neural Radiance Fields, Journal of WSCG, Volume 30 pages 34-43. DOI:10.24132/JWSCG.2022.5. https://arxiv.org/pdf/2205.09351.pdf
Published in arXiv, 2022
Recommended citation: PNeRF: Probabilistic Neural Scene Representations for Uncertain 3D Visual Mapping. Y Ahmine, A Dey, AI Comport - arXiv preprint arXiv:2209.11677, 2022 https://arxiv.org/pdf/2209.11677.pdf
Published in arXiv, 2024
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Master course, University Cote d'Azur, 2021