metadata
license: cc-by-nc-4.0
datasets:
- abo
- inaturalist
pipeline_tag: image-feature-extraction
Model training and evaluation
Instructions for how to train and evaluate a MILE model, as well as the necessary code are in the Amazon Science repository.
Intended use and limitations
These models have been trained on Amazon-Berkeley-Objects and iNaturalist and are intended to demonstrate the power of the object-level embeddings w.r.t. the object /category retrieval task. For other domains or tasks, it should be further fine-tuned on relevant data.
- ABO -
blrp-dinov2-vitl14-reg-lora0-fw-5e-06-mt09996-bs3-800_ckpt0390.pth - iNaturalist -
mile-vitl14-reg-LRx8-g48x8-100M-mt0996-bs3-s250000-ep800-1_ckpt0361.pth
Citation
If you use this work, please cite:
@inproceedings{leotescu2024mile,
title={Self-Supervised Incremental Learning of Object Representations from Arbitrary Image Sets},
author={Leotescu, George and Popa, Alin-Ionut Popa and Grigore, Diana and Voinea, Daniel and Perona, Pietro},
booktitle={Proceedings of WACV},
year={2025}
}
License
This library is licensed under the CC BY NC License.