publications

2026

1. 3DV

   

   MoAngelo: Motion-Aware Neural Surface Reconstruction for Dynamic Scenes

   Mohamed Ebbed and Zorah Lähner

   In International Conference on 3D Vision (3DV), 2026

   Abs arXiv Bib Code Website

   Dynamic scene reconstruction from multi-view videos remains a fundamental challenge in computer vision. While recent neural surface reconstruction methods have achieved remarkable results in static 3D reconstruction, extending these approaches with comparable quality for dynamic scenes introduces significant computational and representational challenges. Existing dynamic methods focus on novel-view synthesis, therefore, their extracted meshes tend to be noisy. Even approaches aiming for geometric fidelity often result in too smooth meshes due to the ill-posedness of the problem. We present a novel framework for highly detailed dynamic reconstruction that extends the static 3D reconstruction method NeuralAngelo to work in dynamic settings. To that end, we start with a high-quality template scene reconstruction from the initial frame using NeuralAngelo, and then jointly optimize deformation fields that track the template and refine it based on the temporal sequence. This flexible template allows updating the geometry to include changes that cannot be modeled with the deformation field, for instance occluded parts or the changes in the topology. We show superior reconstruction accuracy in comparison to previous state-of-the-art methods on the ActorsHQ dataset.

   @inproceedings{ebbed2026moangelo,
     title = {MoAngelo: Motion-Aware Neural Surface Reconstruction for Dynamic Scenes},
     author = {Ebbed, Mohamed and Lähner, Zorah},
     booktitle = {International Conference on 3D Vision (3DV)},
     year = {2026},
   }

2019

1. ICCVW

   

   FuseMODNet: Real-Time Camera and LiDAR based Moving Object Detection for robust low-light Autonomous Driving

   Hazem Rashed, Mohamed Ramzy, Victor Vaquero, and 3 more authors

   In IEEE/CVF International Conference on Computer Vision (ICCV) Workshops, 2019

   arXiv Bib Website

   @inproceedings{rashed2019fusemodnet,
     title = {FuseMODNet: Real-Time Camera and LiDAR based Moving Object Detection for robust low-light Autonomous Driving},
     author = {Rashed, Hazem and Ramzy, Mohamed and Vaquero, Victor and El Sallab, Ahmad and Sistu, Ganesh and Yogamani, Senthil},
     booktitle = {IEEE/CVF International Conference on Computer Vision (ICCV) Workshops},
     year = {2019},
   }

2. NeurIPSW

   

   RST-MODNet: Real-time Spatio-temporal Moving Object Detection for Autonomous Driving

   Mohamed Ramzy, Hazem Rashed, Ahmad El Sallab, and 1 more author

   In Conference on Neural Information Processing Systems (NeurIPS), ML4AD Workshop, 2019

   arXiv Bib

   @inproceedings{ramzy2019rstmodnet,
     title = {RST-MODNet: Real-time Spatio-temporal Moving Object Detection for Autonomous Driving},
     author = {Ramzy, Mohamed and Rashed, Hazem and El Sallab, Ahmad and Yogamani, Senthil},
     booktitle = {Conference on Neural Information Processing Systems (NeurIPS), ML4AD Workshop},
     year = {2019},
   }