SyncNet

This repository contains the demo for the audio-to-video synchronisation network (SyncNet). This network can be used for audio-visual synchronisation tasks including:

1. Removing temporal lags between the audio and visual streams in a video;
2. Determining who is speaking amongst multiple faces in a video.

Please cite the paper below if you make use of the software.

Dependencies

pip install -r requirements.txt

In addition, ffmpeg is required.

Demo

SyncNet demo:

python demo_syncnet.py --videofile data/example.avi --tmp_dir /path/to/temp/directory

Check that this script returns:

AV offset:      3 
Min dist:       5.353
Confidence:     10.021

Full pipeline:

sh download_model.sh
python run_pipeline.py --videofile /path/to/video.mp4 --reference name_of_video --data_dir /path/to/output
python run_syncnet.py --videofile /path/to/video.mp4 --reference name_of_video --data_dir /path/to/output
python run_visualise.py --videofile /path/to/video.mp4 --reference name_of_video --data_dir /path/to/output

Outputs:

$DATA_DIR/pycrop/$REFERENCE/*.avi - cropped face tracks
$DATA_DIR/pywork/$REFERENCE/offsets.txt - audio-video offset values
$DATA_DIR/pyavi/$REFERENCE/video_out.avi - output video (as shown below)

Device Support

This implementation supports both CUDA GPU and CPU execution:

• CUDA GPU: Automatically detected and used if available for faster processing
• CPU: Used as fallback when CUDA is not available, or can be forced for compatibility

Device Selection

The code automatically detects and uses the best available device:

• If CUDA is available → Uses GPU for acceleration
• If CUDA is not available → Falls back to CPU

CPU-Only Execution

To force CPU-only execution (e.g., for compatibility or debugging), you can set:

import os
os.environ['CUDA_VISIBLE_DEVICES'] = ''

Or modify the device selection in the scripts directly.

Publications

@InProceedings{Chung16a,
  author       = "Chung, J.~S. and Zisserman, A.",
  title        = "Out of time: automated lip sync in the wild",
  booktitle    = "Workshop on Multi-view Lip-reading, ACCV",
  year         = "2016",
}