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Code for the Paper Learning Hierarchy Aware Features for Reducing Mistake Severity, accepted in ECCV 2022

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HAF in PyTorch

Official Code Release for Learning Hierarchy Aware Features for Reducing Mistake Severity
Ashima Garg, Depanshu Sani, Saket Anand.

European Conference on Computer Vision (ECCV 2022)

Proposed Approach

Installation

Clone this repository

$ git clone https://github.com/07Agarg/HAF.git
$ cd HAF

Using the Code for Training

The experiments in the paper are contained in the folder experiments/ dataset wise. For CIFAR-100

bash experiments/train/cifar-100/cross-entropy.sh

For iNaturalist-19

bash experiments/train/inat/cross-entropy.sh

For tiered-imagenet

bash experiments/train/tieredimagenet/cross-entropy.sh

For testing

Refer to the code repository: CRM-making-better-mistakes

Link To Trained Models

Download HAF final trained models from the link and use the above repository for testing.

Acknowledgements

This codebase is borrowed from making-better-mistakes

Contact

If you have any suggestion or question, you can leave a message here or contact us directly at ashimag@iiitd.ac.in

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Code for the Paper Learning Hierarchy Aware Features for Reducing Mistake Severity, accepted in ECCV 2022

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