Transfer Learning with Self-Supervised Vision Transformers for Snake Identification

July 08, 2024 · Entered Twilight · 🏛 Conference and Labs of the Evaluation Forum

Repo contents: .gitattributes, .gitignore, .pre-commit-config.yaml, README.md, data, notebooks, pyproject.toml, requirements.txt, scripts, snakeclef, user

Authors Anthony Miyaguchi, Murilo Gustineli, Austin Fischer, Ryan Lundqvist arXiv ID 2407.06178 Category cs.CV: Computer Vision Cross-listed cs.IR, cs.LG Citations 5 Venue Conference and Labs of the Evaluation Forum Repository https://github.com/dsgt-kaggle-clef/snakeclef-2024 ⭐ 4 Last Checked 3 months ago

Abstract

We present our approach for the SnakeCLEF 2024 competition to predict snake species from images. We explore and use Meta's DINOv2 vision transformer model for feature extraction to tackle species' high variability and visual similarity in a dataset of 182,261 images. We perform exploratory analysis on embeddings to understand their structure, and train a linear classifier on the embeddings to predict species. Despite achieving a score of 39.69, our results show promise for DINOv2 embeddings in snake identification. All code for this project is available at https://github.com/dsgt-kaggle-clef/snakeclef-2024.