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@@ -19,7 +19,7 @@ MSI-Net is a visual saliency model that predicts where humans fixate on natural
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  # Datasets
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- Before training the model on fixation data, the encoder weights were initialized from a VGG16 backbone pre-trained on the ImageNet classification task. The model was then trained on the SALICON dataset, which consists of mouse movement recordings as a proxy for gaze measurements. This is the version made available here. Finally, the weights can be fine-tuned on human eye tracking data. MSI-Net was therefore also trained on one of the following datasets:
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  | | Number of Images | Viewers per Image | Viewing Duration | Recording Type |
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  |:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|
 
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  # Datasets
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+ Before training the model on fixation data, the encoder weights were initialized from a VGG16 backbone pre-trained on the ImageNet classification task. The model was then trained on the SALICON dataset, which consists of mouse movement recordings as a proxy for gaze measurements. Finally, the weights can be fine-tuned on human eye tracking data. MSI-Net was therefore also trained on one of the following datasets, although here we only provide the SALICON base model:
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  | | Number of Images | Viewers per Image | Viewing Duration | Recording Type |
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  |:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|