[ICCVW] Logarithm-transform aided Gaussian sampling for Few-Shot Learning

Code implementation of the paper - Logarithm-transform aided Gaussian sampling for Few-Shot Learning (arXiv)

The pretrained checkpoints can be downloaded from - https://drive.google.com/drive/folders/1IjqOYLRH0OwkMZo8Tp4EG02ltDppi61n?usp=sharing

Running the scripts

1. Set up a virtual environment and install the dependencies by running pip install -r requirements.txt
2. Download the pretrained weights from the checkpoints above, and place them in a checkpoints folder in the VI-Priors folder
3. Run distribution calibration by running - python3 evaluate_dc.py
4. Run gaussian-sampling by running python3 gaussian_sampling.py

Citing

If you are using the code/method in your work, please cite the following paper -

@InProceedings{Ganatra_2023_ICCV,
author    = {Ganatra, Vaibhav},
title     = {Logarithm-Transform Aided Gaussian Sampling for Few-Shot Learning},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops},
month     = {October},
year      = {2023},
pages     = {247-252}

References

1. Free Lunch for Few-shot Learning: Distribution Calibration - https://arxiv.org/abs/2101.06395
2. https://github.com/ShuoYang-1998/Few_Shot_Distribution_Calibration/tree/master
3. https://github.com/nupurkmr9/S2M2_fewshot