42 citations · 181 across the 24 of their papers we have counts for
11 papers · 1 filter
Spatially-Adaptive Pixelwise Networks for Fast Image Translation
Tamar Rott Shaham, Michael Gharbi, Richard Zhang +2
We introduce a new generator architecture, aimed at fast and efficient high-resolution image-to-image translation. We design the generator to be an extremely lightweight function o…
Few-shot Image Generation with Elastic Weight Consolidation
Yijun Li, Richard Zhang, Jingwan Lu +1
Few-shot image generation seeks to generate more data of a given domain, with only few available training examples. As it is unreasonable to expect to fully infer the distribution…
StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation
Zongze Wu, Dani Lischinski, Eli Shechtman
We explore and analyze the latent style space of StyleGAN2, a state-of-the-art architecture for image generation, using models pretrained on several different datasets. We first sh…
Look here! A parametric learning based approach to redirect visual attention
Youssef Alami Mejjati, Celso F. Gomez, Kwang In Kim +2
Across photography, marketing, and website design, being able to direct the viewer's attention is a powerful tool. Motivated by professional workflows, we introduce an automatic me…
Swapping Autoencoder for Deep Image Manipulation
Taesung Park, Jun-Yan Zhu, Oliver Wang +4
Deep generative models have become increasingly effective at producing realistic images from randomly sampled seeds, but using such models for controllable manipulation of existing…
High-Resolution Image Inpainting with Iterative Confidence Feedback and Guided Upsampling
Yu Zeng, Zhe Lin, Jimei Yang +3
Existing image inpainting methods often produce artifacts when dealing with large holes in real applications. To address this challenge, we propose an iterative inpainting method w…