This repository contains an unofficial implementation of "Conditional Object-Centric Learning from Video" (ICLR 2022). Note: In this implementation, only unconditional slot intialization is considered.
Paper Link: https://arxiv.org/abs/2111.12594
Clone this repository
git clone https://github.com/a-imamshah/savi-pytorch
cd savi-pytorch
Create new environment
conda create --name savi python=3.8
source activate savi
Install all the dependencies
pip install -r requirements.txt
python train.py
Modify SAViParams
in params.py
to modify the hyperparameters.
To log outputs to wandb, run wandb login YOUR_API_KEY
and set is_logging_enabled=True
in SAViParams
.
Credits to the original authors of the paper: Thomas Kipf, Gamaleldin F. Elsayed, Aravindh Mahendran, Austin Stone,Sara Sabour, Georg Heigold, Rico Jonschkowski, Alexey Dosovitskiy & Klaus Greff.
I adapted this code from the unofficial implementation of "Object-Centric Learning with Slot Attention" by Untitled AI.