/FGDCC

FGDCC: Fine-Grained Deep Cluster Categorization - An Architecture for Intra-Class Variability Problems in FGVC tasks

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FGDCC: Fine-Grained Deep Cluster Categorization - An Architecture for Intra-Class Variability in Problems in FGVC tasks

Method

FGDCC

FGDCC is an architecture developed to tackle intra-class variability problems in FGVC tasks. It operates by performing hierarchical classification of class-wise cluster-assignments conditioned on parent labels (original dataset targets).

Requirements

  • Python 3.8 (or newer)
  • PyTorch 2.0
  • torchvision
  • Faiss
  • Other dependencies: pyyaml, numpy, opencv, submitit, timm

Acknowledgement

This repository is built upon the I-JEPA repository.

License

See the LICENSE file for details about the license under which this code is made available.

Other

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