TSPM

Official repository for "Boosting Audio Visual Question Answering via Key Semantic-Aware Cues" in ACM MM 2024.

ArXiv: https://arxiv.org/abs/2407.20693

Authors: Guangyao Li, Henghui Du, Di Hu

Requirements

python3.6 +
pytorch1.6.0
tensorboardX
ffmpeg
numpy

Usage

1. Clone this repo

   git clone https://github.com/GeWu-Lab/TSPM.git

2. Download data

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

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

3. Feature extraction

   cd feat_script/extract_clip_feat
   python extract_qst_ViT-L14@336px.py
   python extract_qaPrompt_ViT-L14@336px.py
   python extract_token-level_feat.py
   python extract_frames_ViT-L14@336px.py

4. Training

   python -u main_train.py --Temp_Selection --top_k 10 \
   			--Spatio_Perception \
   			--batch-size 64 --epochs 30 --lr 1e-4 \
   			--num_workers 12 --gpu 0,1 \
   			--checkpoint TSPM \
   			--model_save_dir models

5. Testing

   python -u main_test.py --Temp_Selection --top_k 10 \
   		       --Spatio_Perception \
   		       --batch-size 1 --gpu 1 \
   		       --checkpoint TSPM \
   		       --model_save_dir models \
   		       --result_dir results

Citation

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coming soon!

Acknowledgement

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