Final project for the Machine Learning and Artificial Intelligence exam at Politecnico di Torino about Implicit Neural Representation with periodic activation functions (SIREN).
- Abbamonte Matteo (matteoabbamonte)
- Gastaldi Paolo (paologastaldi-polito)
- Gennero Stefano (Stevezbiz)
- Koudounas Alkis (koudounasalkis)
- SIREN implementation
- Image fitting and Poisson reconstruction
- Comparison with ReLU
- Ablation studies
- SISR (single image super resolution)
You can find our report here.
Our presentation slides are here.
All our code is in a Python Notebook format, you can explore it here.
\SIREN
\docs
\papers # papers we referred to
\delivery # our final report, slides and other documents
\results # images, graphs and data we obtained, grouped by experiment type
\src
\include
\siren # content of the original repository we forked from
\mylibs # code we exported from the Python Notebook
\srgan # pretrained SRGAN values and our config for it
...