Model Card for OpenSSL-SimCore
This repo contains some of the pretrained models from our paper, Coreset Sampling from Open-Set for Fine-Grained Self-Supervised Learning. We share the SimCore-pretrained models in the Open-set Self-Supervised Learning (OpenSSL) task, according to each fine-grained dataset. SimCore significantly improves representation learning performance in various downstream tasks, by leveraging a coreset sampled from the unlabeled open-set.
Model Details
Model Sources
- Repository: https://github.com/sungnyun/openssl-simcore
- Paper: Coreset Sampling from Open-Set for Fine-Grained Self-Supervised Learning, S. Kim et al., CVPR 2023
Model Type
SimCore with a stopping criterion (Table 2 in the main paper).
- Backbone: ResNet50
- SSL algorithm: SimCLR
- Open-set: ImageNet-1k
- Target dataset: aircraft, cars, pets, cub, dogs, flowers, stanford40, mit67, dtd, celeba, and food11
For use: Please check our github repo for the instructions.
License: Apache 2.0 License
Where to send questions or comments about the model: https://github.com/sungnyun/openssl-simcore/issues
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