Slot-TTA shows that test-time adaptation using slot-centric models can improve image segmentation on out-of-distribution examples.
-
Updated
Jun 20, 2023 - Python
Slot-TTA shows that test-time adaptation using slot-centric models can improve image segmentation on out-of-distribution examples.
An implementation of several unsupervised object discovery models (Slot Attention, SLATE, GNM) in PyTorch with pre-trained models.
Reimplementation of Slot Attention (object discovery task) in PyTorch with converted checkpoint
[IJCNN 2024] Masked Multi-Query Slot Attention for Unsupervised Object Discovery, 2024 International Joint Conference on Neural Networks
Unsupervised object-centric learning models using Slot Attention in PyTorch.
Unofficial implementation of SAVi in PyTorch
Slot Attention-based Classifier for Explainable Image Recognition
Simple Codebases for Benchmarking Object-Centric Architectures
Add a description, image, and links to the slot-attention topic page so that developers can more easily learn about it.
To associate your repository with the slot-attention topic, visit your repo's landing page and select "manage topics."