no code implementations • 7 Apr 2024 • Jordan Dotzel, Yash Akhauri, Ahmed S. AbouElhamayed, Carly Jiang, Mohamed Abdelfattah, Zhiru Zhang
In this work, we explore the practicality of layer sparsity by profiling residual connections and establish the relationship between model depth and layer sparsity.
no code implementations • 21 Feb 2024 • Jordan Dotzel, Bahaa Kotb, James Dotzel, Mohamed Abdelfattah, Zhiru Zhang
Traditional methods, such as JPEG, perform image compression by operating on structural information, such as pixel values or frequency content.
no code implementations • 18 Dec 2023 • Mahmoud Ahmed, Omer Moussa, Ismail Shaheen, Mohamed Abdelfattah, Amr Abdalla, Marwan Eid, Hesham Eraqi, Mohamed Moustafa
We test this approach on two baseline models: SSAGAN and AttnGAN (with style blocks to enhance the fine-grained details of the images.)
no code implementations • 19 Nov 2022 • Youssef Mohamed, Mohamed Abdelfattah, Shyma Alhuwaider, Feifan Li, Xiangliang Zhang, Kenneth Ward Church, Mohamed Elhoseiny
This paper introduces ArtELingo, a new benchmark and dataset, designed to encourage work on diversity across languages and cultures.
1 code implementation • CVPR 2022 • Dina Bashkirova, Mohamed Abdelfattah, Ziliang Zhu, James Akl, Fadi Alladkani, Ping Hu, Vitaly Ablavsky, Berk Calli, Sarah Adel Bargal, Kate Saenko
Recyclable waste detection poses a unique computer vision challenge as it requires detection of highly deformable and often translucent objects in cluttered scenes without the kind of context information usually present in human-centric datasets.
2 code implementations • ECCV 2020 • Royson Lee, Łukasz Dudziak, Mohamed Abdelfattah, Stylianos I. Venieris, Hyeji Kim, Hongkai Wen, Nicholas D. Lane
Recent works in single-image perceptual super-resolution (SR) have demonstrated unprecedented performance in generating realistic textures by means of deep convolutional networks.