"Masked Multi-Query Slot Attention for Unsupervised Object Discovery" - accepted for oral presentation in 2024 International Joint Conference on Neural Networks Yokohama, Japan.
Access the paper: Arxiv IEEE Xplore
PASCAL VOC 2012 Click here
- Python >= 3.8
- PyTorch >= 1.7.1
- Pytorch Lightning >= 1.1.4
- CUDA enabled computing device
- For more requirements please consult
requirements.txt
- Download the repository and install the required packages:
pip3 install -r requirements.txt
- Unzip the data in a folder of your choice
tar -xf yourdirectory/VOCtrainval_11-May-2012.tar -C $SLURM_TMPDIR/yourdirectory
- The train2 file is sufficent to run the code
torchrun --nproc_per_node=4 --nnodes=1 scripts/train2.py
Edit the parameters before you start in params.py and other required places before you start
@INPROCEEDINGS{pramanik2024masked,
AUTHOR="Rishav Pramanik and Jos{\'e}-Fabian {Villa-V{\'a}squez} and Marco Pedersoli",
TITLE="Masked {Multi-Query} Slot Attention for Unsupervised Object Discovery",
BOOKTITLE="2024 International Joint Conference on Neural Networks (IJCNN) (IJCNN 2024)",
ADDRESS="Yokohama, Japan",
DAYS=28,
MONTH=jun,
YEAR=2024,
}
We greatly thank the authors of https://github.com/amazon-science/object-centric-learning-framework/tree/main and https://github.com/imbue-ai/slot_attention/tree/master for their code which had helped us in our work