This indicates that the model was trained on the VoxCeleb dataset, a large-scale audiovisual dataset containing hundreds of thousands of utterances from thousands of celebrities, extracted from YouTube videos.
This indicates the dataset used to train the model. VoxCeleb is a large-scale audiovisual dataset containing hundreds of thousands of utterances from thousands of celebrities, extracted from YouTube videos. This means the model is exceptionally good at recognizing, tracking, and reconstructing human faces and expressions.
The results are noticeable in practice. The adversarial model ( vox-adv ) is widely considered to produce than its standard counterpart. The difference is so significant that in most applications and tutorials, vox-adv-cpk.pth.tar is the default and recommended choice for achieving the best visual fidelity. Another related file is vox-first-order.pth.tar , which appears to be a variant used in motion co-segmentation tasks.
version is fine-tuned for an additional 50 epochs with an adversarial discriminator to improve the visual quality and realism of the generated faces. Common Applications Questions about the pre-trained models of vox #127 - GitHub 28 Apr 2020 —
Processing multiple frames simultaneously can overload your VRAM. If you experience crashes, lower your batch size to 1 or run the inference on CPU (though it will be significantly slower). Ethical Considerations
This model file is closely associated with two GitHub projects:
This indicates that it is a PyTorch model checkpoint saved as a tar archive, containing the weights, biases, and architecture state of a neural network.