Presentation, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA
Modeling the internal distribution of patches within a single natural image has been long recognized as a powerful prior to many computer vision tasks. However, capturing the distribution of highly diverse datasets with multiple object classes (e.g. ImageNet) is still considered a major challenge and often requires conditioning the generation on another input signal or training the model for a specific task (e.g. super-resolution, inpainting, retargeting).