Progressive Spatio-temporal Perception for Audio-Visual Question Answering (ACMMM'23) [arXiv]

PyTorch code accompanies our PSTP-Net.

Guangyao Li, Wenxuan Hou, Di Hu

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Requirements

python3.6 +
pytorch1.6.0
tensorboardX
ffmpeg
numpy

Usage

1. Clone this repo

   git clone https://github.com/GeWu-Lab/PSTP-Net.git

2. Download data

   MUSIC-AVQA: https://gewu-lab.github.io/MUSIC-AVQA/

   AVQA: http://mn.cs.tsinghua.edu.cn/avqa/

3. Feature extraction

   feat_script/extract_clip_feat
   python extract_patch-level_feat.py

4. Training

   python main_train.py \
   --temp_select True --segs 12 --top_k 2 \
   --spat_select True --top_m 25 \
   --a_guided_attn True \
   --global_local True \
   --batch-size 64 --epochs 30 --lr 1e-4 --gpu 0 \
   --checkpoint PSTP_Net \
   --model_save_dir models_pstp

5. Testing

   python main_test.py

Citation

If you find this work useful, please consider citing it.

coming soon!

Acknowledgement

This research was supported by Public Computing Cloud, Renmin University of China.