[AAAI 2021] MVFNet: Multi-View Fusion Network for Efficient Video Recognition

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Deep LearningMVFNet
Overview

MVFNet: Multi-View Fusion Network for Efficient Video Recognition (AAAI 2021)

1

Overview

We release the code of the MVFNet (Multi-View Fusion Network). The core code to implement the Multi-View Fusion Module is codes/models/modules/MVF.py.

[Mar 24, 2021] We has released the code of MVFNet.

[Dec 20, 2020] MVFNet has been accepted by AAAI 2021.

Prerequisites

All dependencies can be installed using pip:

python -m pip install -r requirements.txt

Our experiments run on Python 3.7 and PyTorch 1.5. Other versions should work but are not tested.

Download Pretrained Models

  • Download ImageNet pre-trained models
cd pretrained
sh download_imgnet.sh
  • Download K400 pre-trained models

Please refer to Model Zoo.

Data Preparation

Please refer to DATASETS.md for data preparation.

Model Zoo

Architecture Dataset T x interval Top-1 Acc. Pre-trained model Train log Test log
MVFNet-ResNet50 Kinetics-400 4x16 74.2% Download link Log link Log link
MVFNet-ResNet50 Kinetics-400 8x8 76.0% Download link Miss Log link
MVFNet-ResNet50 Kinetics-400 16x4 77.0% Download link Log link Log link
MVFNet-ResNet101 Kinetics-400 4x16 76.0% Download link Log link Log link
MVFNet-ResNet101 Kinetics-400 8x8 77.4% Download link Log link Log link
MVFNet-ResNet101 Kinetics-400 16x4 78.4% Download link Log link Log link

Testing

  • For 3 crops, 10 clips, the processing of testing
# Dataset: Kinetics-400
# Architecture: R50_8x8 [email protected]=76.0%
bash scripts/dist_test_recognizer.sh configs/MVFNet/K400/mvf_kinetics400_2d_rgb_r50_dense.py ckpt_path 8 --fcn_testing

Training

This implementation supports multi-gpu, DistributedDataParallel training, which is faster and simpler.

  • For example, to train MVFNet-ResNet50 on Kinetics400 with 8 gpus, you can run:
bash scripts/dist_train_recognizer.sh configs/MVFNet/K400/mvf_kinetics400_2d_rgb_r50_dense.py 8

Acknowledgements

We especially thank the contributors of the mmaction codebase for providing helpful code.

License

This repository is released under the Apache-2.0. license as found in the LICENSE file.

Citation

If you think our work is useful, please feel free to cite our paper 😆 :

@inproceedings{wu2020MVFNet,
  author    = {Wu, Wenhao and He, Dongliang and Lin, Tianwei and Li, Fu and Gan, Chuang and Ding, Errui},
  title     = {MVFNet: Multi-View Fusion Network for Efficient Video Recognition},
  booktitle = {AAAI},
  year      = {2021}
}

Contact

For any question, please file an issue or contact

Wenhao Wu: [email protected]
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Comments
  • Is this right for the test configuration?

    Is this right for the test configuration?

    Hi I noticed your great job for action recognition from AAAI 2021. And I am trying to get the test results as yours on Kinetics400. After I have processed all the test videos to get the frames, I found that there is no annotation processing for kinetics400 test set up, neither in your configuration file. Could you share the test annotation for Kinetics400 and explain why using validation for test? https://github.com/whwu95/MVFNet/blob/ed336228ad88821ffe407a4355017acb416e4670/configs/MVFNet/K400/mvf_kinetics400_2d_rgb_r50_dense.py#L58 https://github.com/whwu95/MVFNet/blob/ed336228ad88821ffe407a4355017acb416e4670/configs/MVFNet/K400/mvf_kinetics400_2d_rgb_r50_dense.py#L145

    ann_file_test = 'datalist/kinetics400/val_ffmpeg_fps30.txt'
...
test=dict(
        type=dataset_type,
        ann_file=ann_file_test,
        data_root=data_root_val,
        pipeline=test_pipeline, 
        test_mode=True,
        modality='RGB',
        filename_tmpl='img_{:05}.jpg'    ))

    Thanks a lot!

    opened by DanLuoNEU 2
  • About online recognition

    About online recognition

    Thank you for your great work. My question is that the mvf module needs to use convolution among multi-view dimensions,especially contains T dimension. If we want to apply the model into online recognition, it is difficult to store too many history frames. So how to apply it to the online recognition?Thank you.

    opened by ohheysherry66 0
Owner
Wenhao Wu
Wenhao Wu
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