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Adversarial Inverse Graphics Networks by Mounir Zarrouk is a document available to read on EtoBox.

What is Adversarial Inverse Graphics Networks about?

The document presents Adversarial Inverse Graphics Networks (AIGNs), a novel approach for learning 2D-to-3D lifting and image-to-image translation using weak supervision from unpaired data. AIGNs utilize feedback from differentiable rendering and distribution matching to improve tasks like 3D human pose estimation and facial image transformation, outperforming traditional supervised models. The architecture allows for creative image generation while accommodating biases in the training data.

Author

Mounir Zarrouk

Language

EN