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20182020
most citedRealistic Hair Simulation Using Image Blending

2 citations · 5 across the 6 of their papers we have counts for

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cs.CV20202 cited

Fast Synthetic LiDAR Rendering via Spherical UV Unwrapping of Equirectangular Z-Buffer Images

Mohammed Hossny, Khaled Saleh, Mohammed Attia +2

LiDAR data is becoming increasingly essential with the rise of autonomous vehicles. Its ability to provide 360deg horizontal field of view of point cloud, equips self-driving vehic…

cs.CV2019

Domain Adaptation for Vehicle Detection from Bird's Eye View LiDAR Point Cloud Data

Khaled Saleh, Ahmed Abobakr, Mohammed Attia +3

Point cloud data from 3D LiDAR sensors are one of the most crucial sensor modalities for versatile safety-critical applications such as self-driving vehicles. Since the annotations…

cs.CV2019

Real-time Intent Prediction of Pedestrians for Autonomous Ground Vehicles via Spatio-Temporal DenseNet

Khaled Saleh, Mohammed Hossny, Saeid Nahavandi

Understanding the behaviors and intentions of humans are one of the main challenges autonomous ground vehicles still faced with. More specifically, when it comes to complex environ…

cs.CV20192 cited

Realistic Hair Simulation Using Image Blending

Mohamed Attia, Mohammed Hossny, Saeid Nahavandi +2

In this presented work, we propose a realistic hair simulator using image blending for dermoscopic images. This hair simulator can be used for benchmarking and validation of the ha…

cs.CV2018

SSIMLayer: Towards Robust Deep Representation Learning via Nonlinear Structural Similarity

Ahmed Abobakr, Mohammed Hossny, Saeid Nahavandi

Deeper convolutional neural networks provide more capacity to approximate complex mapping functions. However, increasing network depth imposes difficulties on training and increase…