This is the code for the paper "Motion-Focused Contrastive Learning of Video Representations" (ICCV'21).

Overview

Motion-Focused Contrastive Learning of Video Representations

Introduction

This is the code for the paper "Motion-Focused Contrastive Learning of Video Representations" (ICCV'21).

Requirements

  • torch == 1.5.1

  • torchvision == 0.6.1

  • liblinear

  • joblib

Data Preparation

You can refer to data_prepare

MCL Pretraining and Linear Evaluation

This implementation only supports multi-gpu, DistributedDataParallel training, which is faster and simpler; single-gpu or DataParallel training is not supported.

Following SeCo, try to download the weights MoCo v2 (200epochs) and put it into the pretrain folder, and run:

  • for UCF101 pretraining and linear evaluation
    bash main_ucf101.sh
  • for Kinetics400 pretraining and linear evaluation
    bash main_kinetics.sh

The checkpoint will be saved in the output/checkpoints entry defined in the configuration file. Besides, the linear evaluation result can be found in output/eval_output_linear.

Downstream task evaluation

  • finetune for UCF101

    cd evaluate/downstream_finetune
    bash run_ucf101.sh
  • finetune for HMDB51

    cd evaluate/downstream_finetune
    bash run_hmdb51.sh

The finetune result can be found in output/eval_output_finetune

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