Deep Metric Loss for Multimodal Learning

Implementation of XXXX 2023 paper Deep Metric Loss for Multimodal Learning.

This repository contains the code and the synthetic data to reproduce the result from the paper:

MultiModal Loss

MultiModalLoss(num_classes, num_modalities, proxies_per_class=20, gamma=0.1)

Parameters:

• num_classes: The number of classes.
• num_modalities: The number of modalities.
• proxies_per_class: The number of proxies per class. The papaer uses 20.
• gamma: Scaling factor.

Prerequisites

• Python (3.7.9)
• PyTorch (1.9.0)
• pytorch_metric_learning (0.9.99)

Acknowledgments

This code is inspired by SoftTriple Loss and pytorch-metric-learning

Citation

If you find the MultiModal Loss is userful, please cite the above paper:

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