While Physics-Based Simulation (PBS) can highly accurately drape a 3D garment model on a 3D body, it remains too costly for real-time applications, such as virtual try-on. By contrast, inference in a deep network, that is, a single forward pass, is typically quite fast. Our goal is to reproduce the results of physically-based simulations by using Deep Nets.
GarNet: A Two-stream Network for Fast and Accurate 3D Cloth Draping
While Physics-Based Simulation (PBS) can highly accurately drape a 3D garment model on a 3D body, it remains too costly for real-time applications, such as virtual try-on. By contrast, inference in a deep network, requiring a single forward pass, is much faster.In this collaborative project with Fision AG, we leverage this property and we propose (…)