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