Neural FFTs for Universal Texture Image Synthesis

no code implementations • NeurIPS 2020 • Morteza Mardani, Guilin Liu, Aysegul Dundar, Shiqiu Liu, Andrew Tao, Bryan Catanzaro

The conventional CNNs, recently adopted for synthesis, require to train and test on the same set of images and fail to generalize to unseen images.

Image Generation Texture Synthesis

Transposer: Universal Texture Synthesis Using Feature Maps as Transposed Convolution Filter

no code implementations • 14 Jul 2020 • Guilin Liu, Rohan Taori, Ting-Chun Wang, Zhiding Yu, Shiqiu Liu, Fitsum A. Reda, Karan Sapra, Andrew Tao, Bryan Catanzaro

Specifically, we directly treat the whole encoded feature map of the input texture as transposed convolution filters and the features' self-similarity map, which captures the auto-correlation information, as input to the transposed convolution.

Texture Synthesis