Various benchmarks related to pedestrian detection, classification, segmentation and path prediction. Pedestrian data as observed from on-board a vehicle in traffic. Mono, stereo and multi-cue.Daimler Pedestrian Segmentation Benchmark DatasetF. Flohr and D. M. Gavrila, PedCut: an iterative framework for pedestrian segmentation combining shape models and multiple data cues, Proc. of the British Machine Vision Conference, Bristol, UK, 2013 (PDF)Daimler Pedestrian Path Prediction Benchmark DatasetN. Schneider and D. M. Gavrila, Pedestrian Path Prediction with Recursive Bayesian Filters: A Comparative Study, In Lecture Notes in Computer Science: Proc. of the German Conference on Pattern Recognition (GCPR), vol. 8142, Springer, 2013 (PDF)Daimler Multi-Cue, Occluded Pedestrian Classification Benchmark DatasetM. Enzweiler, A. Eigenstetter, B. Schiele and D. M. Gavrila, Multi-Cue Pedestrian Classification with Partial Occlusion Handling, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2010Daimler Stereo Pedestrian Detection Benchmark DatasetC. Keller, M. Enzweiler, and D. M. Gavrila, A New Benchmark for Stereo-based Pedestrian Detection, Proc. of the IEEE Intelligent Vehicles Symposium, Baden-Baden, Germany, 2011 (PDF)Daimler Mono Pedestrian Detection Benchmark DatasetM. Enzweiler and D. M. Gavrila, Monocular Pedestrian Detection: Survey and Experiments, IEEE Trans. on Pattern Analysis and Machine Intelligence, vol.31, no.12, pp.2179-2195, 2009 (PDF)Daimler Mono Pedestrian Classification Benchmark DatasetS. Munder and D. M. Gavrila, An Experimental Study on Pedestrian Classification, IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 28, no. 11, pp.1863-1868, Nov. 2006 (PDF)