Daimler Stereo Pedestrian Detection Benchmark C. 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. This new benchmark extends the previously published Daimler Mono Pedestrian Detection Benchmark with 7129 stereo image pairs not containing pedestrians in the training set, from which negative samples can be extracted (positive samples remain unchanged) images of the second camera for the test set (a sequence with more than 21.790 images with 56.492 pedestrian labels, fully visible or partially occluded, captured from a vehicle during a 27 min drive through urban traffic, at VGA resolution (640x480, uncompressed)). vehicle speed and steering angle measurements for the test set, with the yaw rate derived. The dataset specifies an evaluation setting (3D localization criterion, known ground plane, and sensor coverage area provides ROIs). specifies performance metrics both at the frame- and trajectory-level (the latter also allows benchmarking of tracking algorithms). provides the baseline performance of a state-of-the-art method (HOG/linSVM) on the specified training and test set. is open: both training and test set are public and (freely) available for non-commercial purposes, see below.