1 code implementation • 13 Mar 2023 • Rohit Gandikota, Joanna Materzynska, Jaden Fiotto-Kaufman, David Bau
We propose a fine-tuning method that can erase a visual concept from a pre-trained diffusion model, given only the name of the style and using negative guidance as a teacher.
no code implementations • CVPR 2022 • Joanna Materzynska, Antonio Torralba, David Bau
The CLIP network measures the similarity between natural text and images; in this work, we investigate the entanglement of the representation of word images and natural images in its image encoder.
1 code implementation • CVPR 2020 • Joanna Materzynska, Tete Xiao, Roei Herzig, Huijuan Xu, Xiaolong Wang, Trevor Darrell
Human action is naturally compositional: humans can easily recognize and perform actions with objects that are different from those used in training demonstrations.
no code implementations • CVPR 2016 • German Ros, Laura Sellart, Joanna Materzynska, David Vazquez, Antonio M. Lopez
In order to answer this question we have generated a synthetic collection of diverse urban images, named SYNTHIA, with automatically generated class annotations.