1 code implementation • 25 May 2023 • Shady Abu-Hussein, Raja Giryes
In this work, we propose to generalize the denoising diffusion process into an Upsampling Diffusion Probabilistic Model (UDPM).
1 code implementation • 26 Mar 2023 • Dina Bashkirova, Samarth Mishra, Diala Lteif, Piotr Teterwak, Donghyun Kim, Fadi Alladkani, James Akl, Berk Calli, Sarah Adel Bargal, Kate Saenko, Daehan Kim, Minseok Seo, YoungJin Jeon, Dong-Geol Choi, Shahaf Ettedgui, Raja Giryes, Shady Abu-Hussein, Binhui Xie, Shuang Li
To test the abilities of computer vision models on this task, we present the VisDA 2022 Challenge on Domain Adaptation for Industrial Waste Sorting.
no code implementations • 6 Dec 2022 • Shady Abu-Hussein, Tom Tirer, Raja Giryes
In recent years, denoising diffusion models have demonstrated outstanding image generation performance.
1 code implementation • 25 Apr 2022 • Shahaf Ettedgui, Shady Abu-Hussein, Raja Giryes
This new data has a reduced domain gap from the desired target domain, which facilitates the applied UDA approach to close the gap further.
Ranked #5 on Semantic Segmentation on SYNTHIA-to-Cityscapes (using extra training data)
1 code implementation • CVPR 2022 • Sivan Harary, Eli Schwartz, Assaf Arbelle, Peter Staar, Shady Abu-Hussein, Elad Amrani, Roei Herzig, Amit Alfassy, Raja Giryes, Hilde Kuehne, Dina Katabi, Kate Saenko, Rogerio Feris, Leonid Karlinsky
The ability to generalize learned representations across significantly different visual domains, such as between real photos, clipart, paintings, and sketches, is a fundamental capacity of the human visual system.
no code implementations • 4 Feb 2021 • Shady Abu-Hussein, Tom Tirer, Se Young Chun, Yonina C. Eldar, Raja Giryes
In the first one, where no explicit prior is used, we show that the proposed approach outperforms other internal learning methods, such as DIP.