Hawkeye: A PyTorch-based Library for Fine-Grained Image Recognition with Deep Learning

Jiabei He, Yang Shen, Xiu-Shen Wei, Ye Wu
10/14/2023
cs.CV

Official code: Hawkeye-FineGrained/Hawkeye (476 stars, MIT, PyTorch, last commit 2024-05-22).

Abstract

Fine-Grained Image Recognition (FGIR) is a fundamental and challenging task in computer vision and multimedia that plays a crucial role in Intellectual Economy and Industrial Internet applications. However, the absence of a unified open-source software library covering various paradigms in FGIR poses a significant challenge for researchers and practitioners in the field. To address this gap, we present Hawkeye, a PyTorch-based library for FGIR with deep learning. Hawkeye is designed with a modular architecture, emphasizing high-quality code and human-readable configuration, providing a comprehensive solution for FGIR tasks. In Hawkeye, we have implemented 16 state-of-the-art fine-grained methods, covering 6 different paradigms, enabling users to explore various approaches for FGIR. To the best of our knowledge, Hawkeye represents the first open-source PyTorch-based library dedicated to FGIR. It is publicly available at https://github.com/Hawkeye-FineGrained/Hawkeye/, providing researchers and practitioners with a powerful tool to advance their research and development in the field of FGIR.

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Code Implementations(1)

PyTorchMIT

Open source deep learning based fine-grained image recognition toolbox built on PyTorch🔥

47653PythonOct 27, 20222 years agoMIT
deep-learningfine-grainedpytorchtoolbox

Cite this paper

@article{he2023hawkeye,
  title  = {Hawkeye: A PyTorch-based Library for Fine-Grained Image Recognition with Deep Learning},
  author = {Jiabei He and Yang Shen and Xiu-Shen Wei and Ye Wu},
  year   = {2023},
  eprint = {2310.09600},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2310.09600v2}
}

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