986 citations · 1.2k across the 7 of their papers we have counts for
7 papers
Neural Body Fitting: Unifying Deep Learning and Model-Based Human Pose and Shape Estimation
Mohamed Omran, Christoph Lassner, Gerard Pons-Moll +2
Direct prediction of 3D body pose and shape remains a challenge even for highly parameterized deep learning models. Mapping from the 2D image space to the prediction space is diffi…
Joint Graph Decomposition and Node Labeling: Problem, Algorithms, Applications
Evgeny Levinkov, Jonas Uhrig, Siyu Tang +7
We state a combinatorial optimization problem whose feasible solutions define both a decomposition and a node labeling of a given graph. This problem offers a common mathematical a…
The Cityscapes Dataset for Semantic Urban Scene Understanding
Marius Cordts, Mohamed Omran, Sebastian Ramos +6
Visual understanding of complex urban street scenes is an enabling factor for a wide range of applications. Object detection has benefited enormously from large-scale datasets, esp…
How Far are We from Solving Pedestrian Detection?
Shanshan Zhang, Rodrigo Benenson, Mohamed Omran +2
Encouraged by the recent progress in pedestrian detection, we investigate the gap between current state-of-the-art methods and the "perfect single frame detector". We enable our an…
Weakly Supervised Object Boundaries
Anna Khoreva, Rodrigo Benenson, Mohamed Omran +2
State-of-the-art learning based boundary detection methods require extensive training data. Since labelling object boundaries is one of the most expensive types of annotations, the…
Taking a Deeper Look at Pedestrians
Jan Hosang, Mohamed Omran, Rodrigo Benenson +1
In this paper we study the use of convolutional neural networks (convnets) for the task of pedestrian detection. Despite their recent diverse successes, convnets historically under…
Ten Years of Pedestrian Detection, What Have We Learned?
Rodrigo Benenson, Mohamed Omran, Jan Hosang +1
Paper-by-paper results make it easy to miss the forest for the trees.We analyse the remarkable progress of the last decade by discussing the main ideas explored in the 40+ detector…