GSTVQA

Code for 'Learning Generalized Spatial-Temporal Deep Feature Representation for No-Reference Video Quality Assessment'. The code are mostly based on VSFA.

Environment

• Python 3.6.7
• Pytorch 1.6.0 Cuda V9.0.176 Cudnn 7.4.1

Running

• Download the pre-extracted multi-scale VGG features of each datases from BaiduYun, Extraction code: gstv. Then put the features in the path: "./GSTVQA/TCSVT_Release/GVQA_Release/VGG16_mean_std_features/".

• Train:
  python ./GSTVQA/TCSVT_Release/GVQA_Release/GVQA_Cross/main.py --TrainIndex=1 (TrainIndex=1：using the CVD2014 datase as source dataset; 2: LIVE-Qua; 3: LIVE-VQC; 4: KoNviD）

• Test:
  python ./GSTVQA/TCSVT_Release/GVQA_Release/GVQA_Cross/cross_test.py --TrainIndex=1 （TrainIndex=1：using the CVD2014 datase as source dataset; 2: LIVE-Qua; 3: LIVE-VQC; 4: KoNviD）

• The model trained on each above four dataset have been provided in "./GSTVQA/TCSVT_Release/GVQA_Release/GVQA_Cross/models/"