Publications

Publications

Selected Publications

S. Doll, N. Hanselmann, L. Schneider, R. Schulz, M. Cordts, M. Enzweiler, and H. Lensch. DualAD: Disentangling the Dynamic and Static World for End-to-End Driving. IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR), 2024. 

S. Doll, N. Hanselmann, L. Schneider, R. Schulz, M. Enzweiler, and H. P. A. Lensch. S.T.A.R.-Track: Latent Motion Models for End-to-End 3D Object Tracking with Adaptive Spatio-Temporal Appearance Representations. IEEE Robotics and Automation Letters (RA-L), 2023. [Download Publisher PDF –  arXiv ]

S. Doll, R. Schulz, L. Schneider, V. Benzin, M. Enzweiler, and H. P. A. Lensch. SpatialDETR: Robust Scalable Transformer-Based 3D Object Detection from Multi-View Camera Images with Global Cross-Sensor Attention.  European Conference on Computer Vision (ECCV), 2022. [ Download Preprint PDF – Code ]

C. B. Rist, D. Emmerichs, M. Enzweiler, and D. Gavrila. Semantic Scene Completion Using Local Deep Implicit Functions On LiDAR Data. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022. [ arXiv ]

M. Cordts, M. Omran, S. Ramos, T. Rehfeld, M. Enzweiler, R. Benenson, U. Franke, S. Roth, and B. Schiele. The Cityscapes Dataset for Semantic Urban Scene Understanding. Proc. of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, USA, 2016. [ Download Preprint PDF – Download Supplemental PDF – arXiv – Cityscapes Webpage ]

All Journal Publications

S. Doll, N. Hanselmann, L. Schneider, R. Schulz, M. Enzweiler, and H. P. A. Lensch. S.T.A.R.-Track: Latent Motion Models for End-to-End 3D Object Tracking with Adaptive Spatio-Temporal Appearance Representations. IEEE Robotics and Automation Letters (RA-L), 2023. [ Download Publisher PDF –  arXiv ]

C. B. Rist, D. Emmerichs, M. Enzweiler, and D. Gavrila. Semantic Scene Completion Using Local Deep Implicit Functions On LiDAR Data. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022. [Download Publisher PDF –  arXiv ]

M. Cordts, T. Rehfeld, L. Schneider, D. Pfeiffer, M. Enzweiler, S. Roth, M. Pollefeys, and U. Franke. The Stixel World: A Medium-Level Representation of Traffic Scenes. Image and Vision Computing, 2017. [ Download Preprint PDF – arXiv ]

M. Cordts, T. Rehfeld, M. Enzweiler, U. Franke, and S. Roth. Tree-Structured Models for Efficient Scene Labeling. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2016. [ Download Preprint PDF ]

W. Burgard, U. Franke, M. Enzweiler and M. Trivedi. The Mobile Revolution – Machine Intelligence for Autonomous Vehicles (Dagstuhl Seminar 15462). Dagstuhl Reports, vol. 5, no. 11, 2016. [ Download Publisher PDF ]

M. Enzweiler. The Mobile Revolution – Machine Intelligence for Autonomous Vehicles. it – Information Technology, vol. 57, no. 3, pp. 199-202, 2015. [ Download Preprint PDF ]

T. Dang et al. Autonomes Fahren auf der historischen Bertha-Benz Route. tm – Technisches Messen, vol. 82, no. 5, pp. 280-297, 2015. [ Download Preprint PDF ]

J. Ziegler et al. Making Bertha Drive – An Autonomous Journey on a Historic Route. IEEE Intelligent Transportation Systems Magazine, vol. 6, no. 2, pp. 8-20, 2014. [ Download Preprint PDF ]

M. Enzweiler and D. M. Gavrila. A Multi-Level Mixture-of-Experts Framework for Pedestrian Classification. IEEE Transactions on Image Processing, vol. 20, no. 10, pp. 2967-2979, 2011. [ Download Preprint PDF ]

C. G. Keller, M. Enzweiler, M. Rohrbach, D. F. Llorca, C. Schnörr and D. M. Gavrila. The Benefits of Dense Stereo for Pedestrian Detection. IEEE Transactions on Intelligent Transportation Systems, vol. 12, no. 4, pp. 1096-1106, 2011. [ Download Preprint PDF ]

M. Enzweiler and D. M. Gavrila. Monocular Pedestrian Detection: Survey and Experiments. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 31, no. 12, pp. 2179-2195, 2009. [ Download Preprint PDF ]

All Conference and Workshop Publications

S. Doll, N. Hanselmann, L. Schneider, R. Schulz, M. Cordts, M. Enzweiler, and H. Lensch. DualAD: Disentangling the Dynamic and Static World for End-to-End Driving. IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR), 2024. 

M. Voßhans, M. Enzweiler, O. Ait-Aider,  and Y. Mezouar. StixelNExT: Toward monocular low-weight perception for obstacle detection and labeling. IEEE Intelligent Vehicles Symposium (IV), 2024. 

F. Schmidt, F. Holzmüller, M. Kaiser, C. Blessing, and M. Enzweiler. Investigating the Impact of Loop Closing on Visual SLAM Localization Accuracy in Agricultural Applications. International Conference on Advances in Signal Processing and Artificial Intelligence (ASPAI), 2024. (Best Poster Award)

S. Ehrenfeuchter, R. Corlito, R. Marchthaler, and M. Enzweiler. Real-Time Semantic Segmentation for Autonomous Scale Cars using Mixed Real and Synthetic Data. International Conference on Mechatronics and Robotics Engineering (ICMRE), 2024. 

S. Doll, R. Schulz, L. Schneider, V. Benzin, M. Enzweiler, and H. P. A. Lensch. SpatialDETR: Robust Scalable Transformer-Based 3D Object Detection from Multi-View Camera Images with Global Cross-Sensor Attention.  European Conference on Computer Vision (ECCV), 2022. [ Download Preprint PDF – Code ]

C. B. Rist, D. Schmidt, M. Enzweiler, and D. M. Gavrila. SCSSnet: Learning Spatially-Conditioned Scene Segmentation on LiDAR Point Clouds.  IEEE Intelligent Vehicles Symposium (IV), 2020. (Best Paper Award)Download Preprint PDF ]

C. B. Rist, M. Enzweiler, and D. M. Gavrila. Cross-Sensor Deep Domain Adaptation for LiDAR Detection and Segmentation. IEEE Intelligent Vehicles Symposium (IV), 2019. [ Download Preprint PDF ]

L. T. Triess, D. Peter, C. B. Rist, M. Enzweiler, and J. M. Zöllner. CNN-based synthesis of realistic high-resolution LiDAR data. IEEE Intelligent Vehicles Symposium (IV), 2019. [ arXiv ]

F. Piewak, P. Pinggera, M. Enzweiler, D. Pfeiffer, and J. M. Zöllner. Improved Semantic Stixels via Multimodal Sensor Fusion. German Conference on Pattern Recognition (GCPR), Stuttgart, Germany, 2018. [ arXiv ]

F. Piewak, P. Pinggera, M. Schäfer, D. Peter, B. Schwarz, N. Schneider, M. Enzweiler, D. Pfeiffer, and J. M. Zöllner. Boosting LiDAR-Based Semantic Labeling by Cross-Modal Training Data Generation. ECCV Workshop on Multimodal Learning and Applications, 2018. [ arXiv ]

M. Cordts, M. Omran, S. Ramos, T. Rehfeld, M. Enzweiler, R. Benenson, U. Franke, S. Roth, and B. Schiele. The Cityscapes Dataset for Semantic Urban Scene Understanding. Proc. of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, USA, 2016. [ Download Preprint PDF – Download Supplemental PDF – arXiv – Cityscapes Webpage ]

L. Schneider, M. Cordts, T. Rehfeld, D. Pfeiffer, M. Enzweiler, U. Franke, M. Pollefeys, and S. Roth. Semantic Stixels: Depth is Not Enough. IEEE Intelligent Vehicles Symposium, 2016. (Best Paper Award). Download Preprint PDF ]

M. Kehl, M. Enzweiler, B. Fröhlich, U. Franke and W. Heiden. Vision-based Road Sign Detection. International Conference on Intelligent Transportations Systems (ITSC), 2015. [ Download Preprint PDF ]

D. Savastürk, B. Fröhlich, N. Schneider, M. Enzweiler and U. Franke. A Comparison Study on Vehicle Detection in Far Infrared and Regular Images. International Conference on Intelligent Transportations Systems (ITSC), 2015. [ Download Preprint PDF ]

J. Tao, M. Enzweiler, U. Franke, D. Pfeiffer and R. Klette. What is in Front? Multiple-Object Detection and Tracking with Dynamic Occlusion Handling. International Conference on Computer Analysis of Images and Patterns (CAIP), 2015. [ Download Preprint PDF ]

M. Cordts, M. Omran, S. Ramos, T. Scharwächter, M. Enzweiler, R. Benenson, U. Franke, S. Roth, and B. Schiele. The Cityscapes dataset. CVPR Workshop on The Future of Datasets in Vision, Boston, USA, 2015. [ Download Preprint PDF ]

T. Scharwächter, M. Enzweiler, U. Franke and S. Roth. Stixmantics: A Medium-Level Model for Real-Time Semantic Scene Understanding. European Conference on Computer Vision (ECCV), Zurich, Switzerland, 2014. [ Download Preprint PDF ]

M. Cordts, L. Schneider, M. Enzweiler, U. Franke and S. Roth. Object-level Priors for Stixel Generation. German Conference on Pattern Recognition (GCPR), Münster, Germany, 2014. [ Download Preprint PDF ]

B. Fröhlich, M. Enzweiler, and U. Franke. Will this Car Change the Lane ? – Turn Signal Recognition in the Frequency Domain. IEEE Intelligent Vehicles Symposium, 2014. (Best Paper Award). Download Preprint PDF ]

U. Franke, D. Pfeiffer, C. Rabe, C. Knoeppel, M. Enzweiler, F. Stein, R. G. Herrtwich. Making Bertha See. ICCV Workshop on Computer Vision for Autonomous Driving, Sydney, Australia, 2013. Download Preprint PDF ]

T. Scharwächter, M. Enzweiler, U. Franke and S. Roth. Efficient Multi-Cue Scene Segmentation. German Conference on Pattern Recognition (GCPR), Saarbrücken, Germany, 2013, (GCPR 2013 Main Prize). Download Preprint PDF ]

M. Enzweiler, P. Greiner, C. Knoeppel and U. Franke. Towards Multi-Cue Urban Curb Recognition. IEEE Intelligent Vehicles Symposium, Gold Coast, Australia, 2013. [ Download Preprint PDF ]

M. Enzweiler, M. Hummel, D. Pfeiffer and U. Franke. Efficient Stixel-Based Object Recognition. IEEE Intelligent Vehicles Symposium, Alcala de Henares, Spain, 2012. [ Download Preprint PDF ]

C. G. Keller, M. Enzweiler and D. M. Gavrila. A New Benchmark for Stereo-Based Pedestrian Detection. IEEE Intelligent Vehicles Symposium, Baden-Baden, Germany, 2011. [ Download Preprint PDF ]

M. Enzweiler and D. M. Gavrila. Integrated Pedestrian Classification and Orientation Estimation. Proc. of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), San Francisco, USA, 2010. [ Download Preprint PDF ]

M. Enzweiler, A. Eigenstetter, B. Schiele and D. M. Gavrila. Multi-Cue Pedestrian Classification with Partial Occlusion Handling. Proc. of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), San Francisco, USA, 2010. [ Download Preprint PDF ]

M. Rohrbach, M. Enzweiler and D. M. Gavrila. High-Level Fusion of Depth and Intensity for Pedestrian Classification. DAGM Symposium, pp. 101-110, Jena, Germany, 2009. [ Download Preprint PDF ]

M. Enzweiler and D. M. Gavrila. A Mixed Generative-Discriminative Framework for Pedestrian Classification. Proc. of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Anchorage, USA, 2008. [ Download Preprint PDF ]

M. Enzweiler, P. Kanter and D. M. Gavrila. Monocular Pedestrian Recognition Using Motion Parallax. IEEE Intelligent Vehicles Symposium, Eindhoven, The Netherlands, 2008. [ Download Preprint PDF ]

W. Schulz, M. Enzweiler and T. Ehlgen. Pedestrian Recognition from a Moving Catadioptric Camera. DAGM Symposium, pp. 456-465, Heidelberg, Germany, 2007. [ Download Preprint PDF ]

M. Enzweiler, R. P Wildes and R. Herpers. Unified Target Detection and Tracking Using Motion Coherence. IEEE Workshop on Motion and Video Computing, pp. 66-71, Breckenridge, USA, 2005. [ Download Preprint PDF ]

Theses

M. Enzweiler. Compound Models for Vision-Based Pedestrian Recognition. PhD Thesis, University of Heidelberg, Heidelberg, Germany, 05/2011.

M. Enzweiler. Resampling Techniques for Pedestrian Classification. Master’s Thesis, University of Ulm, Ulm, Germany, 12/2005.

M. Enzweiler. Computing Motion Trajectories Using Spatiotemporal Motion Analysis. Bachelor’s Thesis, Bonn-Rhein-Sieg University of Applied Sciences, St. Augustin, Germany, 08/2003.


This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author’s copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

Comments are closed.