upupbo / GSTVQA

Code for 'Learning Generalized Spatial-Temporal Deep Feature Representation for No-Reference Video Quality Assessment'

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GSTVQA

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

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/"

About

Code for 'Learning Generalized Spatial-Temporal Deep Feature Representation for No-Reference Video Quality Assessment'


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