no code implementations • 9 Aug 2023 • Nina Merkle, Reza Bahmanyar, Corentin Henry, Seyed Majid Azimi, Xiangtian Yuan, Simon Schopferer, Veronika Gstaiger, Stefan Auer, Anne Schneibel, Marc Wieland, Thomas Kraft
In order to respond effectively in the aftermath of a disaster, emergency services and relief organizations rely on timely and accurate information about the affected areas.
no code implementations • 19 Oct 2020 • Seyed Majid Azimi, Maximilian Kraus, Reza Bahmanyar, Peter Reinartz
We also describe our proposed Deep Learning based Multi-Object Tracking method AerialMPTNet that fuses appearance, temporal, and graphical information using a Siamese Neural Network, a Long Short-Term Memory, and a Graph Convolutional Neural Network module for a more accurate and stable tracking.
no code implementations • 12 Jul 2020 • Seyed Majid Azimi, Corentin Henry, Lars Sommer, Arne Schumann, Eleonora Vig
We have defined two main tasks on this dataset: dense semantic segmentation and multi-class lane-marking prediction.
no code implementations • 12 Jul 2020 • Seyed Majid Azimi, Reza Bahmanyar, Corenin Henry, Franz Kurz
To address this issue, we introduce EAGLE (oriEnted vehicle detection using Aerial imaGery in real-worLd scEnarios), a large-scale dataset for multi-class vehicle detection with object orientation information in aerial imagery.
no code implementations • 27 Jun 2020 • Maximilian Kraus, Seyed Majid Azimi, Emec Ercelik, Reza Bahmanyar, Peter Reinartz, Alois Knoll
Due to the challenges such as the large number and the tiny size of the pedestrians (e. g., 4 x 4 pixels) with their similar appearances as well as different scales and atmospheric conditions of the images with their extremely low frame rates (e. g., 2 fps), current state-of-the-art algorithms including the deep learning-based ones are unable to perform well.
no code implementations • ICCV 2019 • Seyed Majid Azimi, Corentin Henry, Lars Sommer, Arne Schumann, Eleonora Vig
We have defined two main tasks on this dataset: dense semantic segmentation and multi-class lane-marking prediction.
Ranked #1 on Semantic Segmentation on SkyScapes-Lane
no code implementations • 15 Nov 2018 • Seyed Majid Azimi
On-board real-time vehicle detection is of great significance for UAVs and other embedded mobile platforms.
no code implementations • 7 Jul 2018 • Seyed Majid Azimi, Eleonora Vig, Reza Bahmanyar, Marco Körner, Peter Reinartz
During training, we minimize joint horizontal and oriented bounding box loss functions, as well as a novel loss that enforces oriented boxes to be rectangular.
Ranked #49 on Object Detection In Aerial Images on DOTA (using extra training data)
no code implementations • 19 Mar 2018 • Seyed Majid Azimi, Peter Fischer, Marco Körner, Peter Reinartz
Therefore, accurate and reliable lane marking semantic segmentation in the imagery of roads and highways is needed to achieve such goals.
no code implementations • 5 Feb 2018 • Corentin Henry, Seyed Majid Azimi, Nina Merkle
Remote sensing is extensively used in cartography.
no code implementations • 20 Jun 2017 • Seyed Majid Azimi, Dominik Britz, Michael Engstler, Mario Fritz, Frank Mücklich
In this work, we propose a Deep Learning method for microstructural classification in the examples of certain microstructural constituents of low carbon steel.