IGNOR: Image-guided Neural Object Rendering

Understand

We propose a learned image-guided rendering technique that combines the benefits of image-based rendering and GAN-based image synthesis.

• The goal of our method is to generate photo-realistic re-renderings of reconstructed objects for virtual and augmented reality applications (e.g., virtual showrooms, virtual tours \& sightseeing, the digital inspection of historical artifacts).
• A core component of our work is the handling of view-dependent effects.
• Specifically, we directly train an object-specific deep neural network to synthesize the view-dependent appearance of an object.