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Real‐time Virtual‐Try‐On from a Single Example Image through Deep Inverse Graphics and Learned Differentiable Renderers
Abstract Augmented reality applications have rapidly spread across online retail platforms and social media, allowing consumers to virtually try‐on a large variety of products, such as makeup, hair dying, or shoes. However, parametrizing a renderer to synthesize realistic images of a given product remains a challenging task that requires expert …