Official MMANet in PyTorch

Here is the official PyTorch implementation of MMANet proposed in ''MMANet: Margin-aware Distillation and Modality-aware Regularization for Incomplete Multimodal Learning''.

It's a general framework to address the issue of multimodal learning with incomplete data. Details can be seen in our CVPR 2023 paper.

Basic information of implementation

Main Dependencies

• Ubuntu20.04
• CUDA 11.3
• Pytorch1.12.1
• Python 3.8
• requirements
  • pip install -r requirements.txt

Folder introduction

Our paper perform experiments on two classic multimodal tasks, e.g classification and segmentation.

The coressponding codes are deployed in classification and segmentation folders. contains multimodal classification and segmentation tasks.

Performance on multimodal classificaition task

Details can be seen in Classification

Performance on multimodal segmentation task

Details can be seen in Segmentation