This repository is re-implementation of CSQ(Central Similarity Quantization) with MFNet(Multi-Fiber Net)
CSQ is a methodology for video retrieval, and in this repository, we use the UCF101 dataset to conduct video retrieval.

1. Get the code.

  git clone https://github.com/Jo-won/CSQ_pytorch.git

2. Check requirement.txt

3. Go to Wandb and create an account.
   
   
   
   

Running this code requires UCF101 dataset. (available here)
The data path can be checked below.
Please move trainlist01_ilp.txt and testlist01_ilp.txt inside ucf101_txt folder

<DATA_PATH>

+-- DATA_ROOT
|   +-- video
|   |   +-- ApplyEyeMakeup
|   |   |   +-- v_ApplyEyeMakeup_g01_c01.avi
|   |   |   +-- ...
|   |   +-- ApplyLipstick
|   |   +-- ...
|   +-- ucfTrainTestlist
|   |   +-- trainlist01_ilp.txt
|   |   +-- testlist01_ilp.txt

• Train & Vaild
  Please set the model_root folder to be saved at opt.py,
  set the data_root in the train_ucf101_base.sh file,
  and then use the command below.
  Validation proceeds with the same videos as the test.

bash train_ucf101_base.sh

• Result
  When CSQ 64bits,

• CSQ official code : https://github.com/yuanli2333/Hadamard-Matrix-for-hashing
• MFNet official code : https://github.com/cypw/PyTorch-MFNet