1 citations · 2 across the 5 of their papers we have counts for
5 papers
Towards Discriminative and Transferable One-Stage Few-Shot Object Detectors
Karim Guirguis, Mohamed Abdelsamad, George Eskandar +4
Recent object detection models require large amounts of annotated data for training a new classes of objects. Few-shot object detection (FSOD) aims to address this problem by learn…
CFA: Constraint-based Finetuning Approach for Generalized Few-Shot Object Detection
Karim Guirguis, Ahmed Hendawy, George Eskandar +3
Few-shot object detection (FSOD) seeks to detect novel categories with limited data by leveraging prior knowledge from abundant base data. Generalized few-shot object detection (G-…
An Unsupervised Domain Adaptive Approach for Multimodal 2D Object Detection in Adverse Weather Conditions
George Eskandar, Robert A. Marsden, Pavithran Pandiyan +3
Integrating different representations from complementary sensing modalities is crucial for robust scene interpretation in autonomous driving. While deep learning architectures that…
USIS: Unsupervised Semantic Image Synthesis
George Eskandar, Mohamed Abdelsamad, Karim Armanious +1
Semantic Image Synthesis (SIS) is a subclass of image-to-image translation where a photorealistic image is synthesized from a segmentation mask. SIS has mostly been addressed as a…
SLPC: a VRNN-based approach for stochastic lidar prediction and completion in autonomous driving
George Eskandar, Alexander Braun, Martin Meinke +2
Predicting future 3D LiDAR pointclouds is a challenging task that is useful in many applications in autonomous driving such as trajectory prediction, pose forecasting and decision…