Search Results for author: Emec Ercelik

Found 2 papers, 0 papers with code

A Survey of Robust 3D Object Detection Methods in Point Clouds

no code implementations31 Mar 2022 Walter Zimmer, Emec Ercelik, Xingcheng Zhou, Xavier Jair Diaz Ortiz, Alois Knoll

The purpose of this work is to review the state-of-the-art LiDAR-based 3D object detection methods, datasets, and challenges.

Autonomous Driving Data Augmentation +3

AerialMPTNet: Multi-Pedestrian Tracking in Aerial Imagery Using Temporal and Graphical Features

no code implementations27 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.

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