no code implementations • 23 Jun 2023 • George Eskandar, Shuai Zhang, Mohamed Abdelsamad, Mark Youssef, Diandian Guo, Bin Yang
Data efficiency, or the ability to generalize from a few labeled data, remains a major challenge in deep learning.
1 code implementation • IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2022 • George Eskandar, Mohamed Abdelsamad, Karim Armanious, Shuai Zhang, Bin Yang
Semantic Image Synthesis (SIS) is a subclass of image-to-image translation where a semantic layout is used to generate a photorealistic image.
Ranked #11 on Image-to-Image Translation on ADE20K Labels-to-Photos
Multimodal Unsupervised Image-To-Image Translation Translation +1
no code implementations • 11 Oct 2022 • Karim Guirguis, Mohamed Abdelsamad, George Eskandar, Ahmed Hendawy, Matthias Kayser, Bin Yang, Juergen Beyerer
We make the observation that the large gap in performance between two-stage and one-stage FSODs are mainly due to their weak discriminability, which is explained by a small post-fusion receptive field and a small number of foreground samples in the loss function.
Ranked #13 on Few-Shot Object Detection on MS-COCO (10-shot)
no code implementations • 11 Apr 2022 • Karim Guirguis, Ahmed Hendawy, George Eskandar, Mohamed Abdelsamad, Matthias Kayser, Juergen Beyerer
In this work, we propose a constraint-based finetuning approach (CFA) to alleviate catastrophic forgetting, while achieving competitive results on the novel task without increasing the model capacity.
Ranked #8 on Few-Shot Object Detection on MS-COCO (10-shot)
1 code implementation • 29 Sep 2021 • George Eskandar, Mohamed Abdelsamad, Karim Armanious, Bin Yang
Semantic Image Synthesis (SIS) is a subclass of image-to-image translation where a photorealistic image is synthesized from a segmentation mask.