4 citations · 9 across the 5 of their papers we have counts for
6 papers · 1 filter
ST-DETR: Spatio-Temporal Object Traces Attention Detection Transformer
Eslam Mohamed, Ahmad El-Sallab
We propose ST-DETR, a Spatio-Temporal Transformer-based architecture for object detection from a sequence of temporal frames. We treat the temporal frames as sequences in both spac…
MODETR: Moving Object Detection with Transformers
Eslam Mohamed, Ahmad El-Sallab
Moving Object Detection (MOD) is a crucial task for the Autonomous Driving pipeline. MOD is usually handled via 2-stream convolutional architectures that incorporates both appearan…
Spatio-Temporal Multi-Task Learning Transformer for Joint Moving Object Detection and Segmentation
Eslam Mohamed, Ahmed El-Sallab
Moving objects have special importance for Autonomous Driving tasks. Detecting moving objects can be posed as Moving Object Segmentation, by segmenting the object pixels, or Moving…
INSTA-YOLO: Real-Time Instance Segmentation
Eslam Mohamed, Abdelrahman Shaker, Ahmad El-Sallab +1
Instance segmentation has gained recently huge attention in various computer vision applications. It aims at providing different IDs to different object of the scene, even if they…
Generalized Object Detection on Fisheye Cameras for Autonomous Driving: Dataset, Representations and Baseline
Hazem Rashed, Eslam Mohamed, Ganesh Sistu +4
Object detection is a comprehensively studied problem in autonomous driving. However, it has been relatively less explored in the case of fisheye cameras. The standard bounding box…
Monocular Instance Motion Segmentation for Autonomous Driving: KITTI InstanceMotSeg Dataset and Multi-task Baseline
Eslam Mohamed, Mahmoud Ewaisha, Mennatullah Siam +5
Moving object segmentation is a crucial task for autonomous vehicles as it can be used to segment objects in a class agnostic manner based on their motion cues. It enables the dete…