Picture of Emec Ercelik

Emec Ercelik

Technical University of Munich

Postal address

Boltzmannstr. 3
85748 Garching b. München

Curriculum Vitae

  • (2017 -Now) Ph.D. candidate, Technical University of Munich
  • (2013-2016) Master of Science Degree in Electronics Engineering, Istanbul Technical University
  • (2008-2013) Bachelor's Degree in Electronics Engineering, Istanbul Technical University

Research Interests

Object Detection, Sensor Fusion, Temporal data processing with deep learning models


Temporal Data Processing for 3D Object Detection in Autonomous Driving

Self-supervised Scene Flow-based 3D Object Detection

We aim to use temporal features learned through self-supervised scene flow task for 3D object detection. Please check our paper published in ECCV 2022. Also, our codes can be reached on Github.


Multi-frame Object-level 3D Object Detection

We aim to aggregate regional object features from multiple frames to obtain more representative temporal features that can be used for more accurate 3D detections. Please check our papers published in IEEE Intelligent Vehicles Symposium 2021 and IEEE Access in 2021. Also, our codes can be reached on Github.

Open Thesis Topics / Guided Research

Thanks for your interest. I will no longer be able to provide thesis topics.

Thesis Supervision



  • Guided research: Self-supervised scene flow approaches for 3D lidar point clouds, Zhijie Yang, Nov.2021-Sep.2022
  • Guided research: Analysis of flow-based 3D perception tasks, Hanzhen Zhang, Dec. 2021-Jun.2022
  • Master's thesis: Spatio-temporal Graph Neural Networks for Object Detection, Maximilian Listl, Nov. 2021-Jun.2022
  • Master's thesis: Self-supervised 3D Multi-object Tracking, Burak Tomruk, Nov. 2021-May 2022
  • Master's thesis: Multi-frame self-supervised 3D object detection, Pınar Topçam, Nov. 2021-May 2022
  • Bachelor's thesis: Analysis of Self-supervised Scene Flow for Perception, Aysu Konyala, Nov. 2021-Apr.2022
  • Master's thesis: Spatio-temporal Graph Neural Networks for 3D Object Detection, Mingyu Liu, Oct. 2021-Feb.2022
  • Master's thesis: Attention-based Temporal Frustum Pointnet for 3D Object Detection, Sebastian Grauff, Apr.2021-Jan.2022
  • Master's thesis: Multi-Person and Vehicle Detection and Tracking in Aerial Imagery Sequences using Deep Learning Algorithms, Tsuyoshi Beheim, Apr.2021-Nov.2021
  • Bachelor's thesis: Transfer learning for Temporal 3D Object Detection, Kaan Yılmaz Çaylı, Apr.2021-Aug.2021
  • Bachelor's thesis: Improving orientation estimation for Radar-based object detection, Taner Kurt, Nov.2020-May2021
  • Guided research: Novel methods and challenges of processing time-series data for object detection, Sadık Ekin Özbay, Nov. 2020-Mar.2021
  • Master's thesis: Analysis of 3D Object Association Methods for RGB-D Data, Patrick von Haller, Jun.2020-Feb.2021
  • Master's thesis: 3D object tracking combining LiDAR with temporal image cues, Eda Çiçek, Apr.2020-Dec.2020
  • Bachelor's thesis: Analysis of proposal improvement on Faster RCNN, Salma Mrabet, Jul.2020-Nov2020
  • Master's thesis: 3D object detection using temporal data fusion, Zhiran Yan, Jan.2020-Jul.2020
  • Master's thesis: Efficient object detection and tracking for indoor applications, Robert Walter, Nov.2019-May2020
  • Master's thesis: Multi-Object Tracking in Aerial and Satellite Imagery, Maximilian Kraus, Nov.2019-May2020
  • Master's thesis: Processing video data to improve 2D object detection, Arnd Pettirsch, Oct. 2019-Apr.2020
  • Master's thesis: Deep Learning based People Counting Using 60 GHz FMCW Radar Sensor, Cem Yusuf Aydoğdu, Oct. 2019-Apr.2020
  • Master's thesis: Data fusion from heterogeneous sensor for indoor scenarios, Okan Kamil Şen, Sep.2019-Mar.2020
  • Master's thesis: Radar-based object detection using deep neural networks, Maria Dreher, Jun.2019-Dec.2019
  • Master's thesis: Motion cueing for the control of a car simulator using RNN and RL, Ahmet Burakhan Koyuncu, Apr.2019-Nov.2019
  • Master's thesis: Sensor fusion for object detection on simulator data, Tuba Topaloğlu, Feb.2019-Nov.2019
  • Master's thesis: Sensor fusion through 3D proposals using data generated from simulators, Ruslan Noschajew, Apr.2019-Oct.2019
  • Research internship: Integration of depth information for LSTM-based online video object detection, Mert Keser, Mar.2019-Apr.2019
  • Bachelor's thesis: The recognition and evaluation of traffic signs and its additional information with machine learning in the context of autonomous driving, Tobias Weber, Nov.2018-Apr.2019
  • Guided research: Methods to transfer knowledge from simulation into real-world for object detection problem, Anshul Sharma, Nov.2018-Apr.2019
  • Master's thesis: Evaluation of an object detection model adding recurrency, Daniel Haller, Nov.2018-Apr.2019


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Previous semesters

  • Visual feature learning in autonomous driving (SS 2019)
  • Multimodal Temporal Data Processing in Autonomous Driving (WS19/20)
  • Visual feature learning in autonomous driving (SS 2020)
  • Multimodal Temporal Data Processing in Autonomous Driving (WS 20/21)
  • Visual feature learning in autonomous driving (SS 2021)



  • Erçelik, Emeç; Yurtsever, Ekim; Liu, Mingyu; Yang, Zhijie; Zhang, Hanzhen; Topçam, Pınar; Listl, Maximilian; Kaan Çaylı, Yılmaz; Knoll, Alois: 3D Object Detection with a Self-supervised Lidar Scene Flow Backbone. European conference on computer vision (ECCV), 2022 mehr… BibTeX Volltext ( DOI ) Volltext (mediaTUM)


  • Emeç Erçelik; Ekim Yurtsever; Alois Knoll: Temp-Frustum Net: 3D Object Detection with Temporal Fusion. 2021 IEEE Intelligent Vehicles Symposium (IV), 2021 mehr… BibTeX Volltext ( DOI ) Volltext (mediaTUM)
  • Ercelik, Emec; Yurtsever, Ekim; Knoll, Alois: 3D Object Detection with Multi-Frame RGB-Lidar Feature Alignment. IEEE Access, 2021, 1-1 mehr… BibTeX Volltext ( DOI ) Volltext (mediaTUM)
  • Feryel Zoghlami; Okan Kamil Sen; Harald Heinrich; Germar Schneider; Emec Ercelik; Alois Knoll; Thomas Villman: ToF/Radar early feature-based fusion system for human detection and tracking. 22nd IEEE International Conference on Industrial Technology (ICIT 2021), 2021 mehr… BibTeX Volltext (mediaTUM)


  • Ahmet Burakhan Koyuncu; Emec Ercelik; Eduard Comulada-Simpson; Joost Venrooij; Mohsen Kaboli; Alois Knoll: A Novel Approach to Neural Network-based Motion Cueing Algorithm for a Driving Simulator. 31st IEEE Intelligent Vehicles Symposium, 2020 mehr… BibTeX Volltext (mediaTUM)
  • Maria Dreher; Emec Ercelik; Timo Bänziger; Alois Knoll: Radar-based 2D Car Detection Using Deep Neural Networks. 23rd Intelligent Transportation Systems Conference (ITSC 2020), 2020 mehr… BibTeX Volltext (mediaTUM)
  • Maximilian Kraus; Seyed Majid Azimi; Emec Ercelik; Reza Bahmanyar; Peter Reinartz; Alois Knoll: AerialMPTNet: Multi-Pedestrian Tracking in Aerial Imagery Using Temporal and Graphical Features. 25th International Conference on Pattern Recognition (ICPR 2020), 2020 mehr… BibTeX Volltext (mediaTUM)


  • Tobias Weber; Emec Ercelik; Martin Ebert; Alois Knoll: Recognition & Evaluation of Additional Traffic Signs on the example of '80 km/h when wet'. 2019 IEEE Intelligent Transportation Systems Conference (ITSC), 2019 mehr… BibTeX Volltext ( DOI )


  • Zied Tayeb, Emeç Erçelik, Jörg Conradt: Decoding of motor imagery movements from EEG signals using SpiNNaker neuromorphic hardware. Neural Engineering (NER), 2017 8th International IEEE/EMBS Conference on, 2017 mehr… BibTeX Volltext ( DOI ) Volltext (mediaTUM)


  • Emeç Erçelik, Neslihan Serap Şengör: A neurocomputational model implemented on humanoid robot for learning action selection. Neural Networks (IJCNN), 2015 International Joint Conference on, 2015 mehr… BibTeX Volltext ( DOI ) Volltext (mediaTUM)
  • Emeç Erçelik, Rahmi Elibol, Neslihan Serap Şengör: A model on building and modifying the stimulus action association in the brain. Signal Processing and Communications Applications Conference (SIU), 2015 23th, 2015 mehr… BibTeX Volltext ( DOI ) Volltext (mediaTUM)