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The gpen model is an image-to-image translation model trained to restore the facial details in blurry or low resolution images. It is specifically designed to work well in real-world scenarios with diverse and challenging conditions. The model is capable of automatically enhancing facial features, such as eyes, nose, and mouth, to produce visually pleasing and realistic results. It can be used for various applications, including image post-processing, video enhancement, and facial recognition tasks.

Use cases

The gpen model has a wide range of potential use cases for various industries. For image post-processing, this model can be used to enhance the quality of images taken in low light conditions or from a distance, making them more suitable for professional use or social media sharing. In video enhancement, the gpen model can be applied to improve the visibility and clarity of faces in surveillance footage, making it easier to identify individuals. In facial recognition tasks, the model can enhance facial details to improve the accuracy of recognition systems, which could be valuable in security and authentication applications. Moreover, the gpen model can be integrated into smartphone cameras or photo editing software to provide users with an easy and efficient way to enhance the quality of their photos. Overall, this AI model has the potential to revolutionize the way we capture, process, and utilize images in various fields.



Cost per run
Avg run time
Nvidia T4 GPU

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Summary of this model and related resources.

Model NameGpen
Blind Face Restoration in the Wild
Model LinkView on Replicate
API SpecView on Replicate
Github LinkView on Github
Paper LinkView on Arxiv


How popular is this model, by number of runs? How popular is the creator, by the sum of all their runs?

Model Rank
Creator Rank


How much does it cost to run this model? How long, on average, does it take to complete a run?

Cost per Run$0.0033
Prediction HardwareNvidia T4 GPU
Average Completion Time6 seconds