In this paper, we present a novel approach, called Deep MANTA (Deep Many-Tasks), for
many-task vehicle analysis from a given image. A robust convolutional network is introduced …

While 3D object representations are being revived in the context of multi-view object class
detection and scene understanding, they have not yet attained wide-spread use in fine …

We present a method to infer 3D pose and shape of vehicles from a single image. To tackle
this ill-posed problem, we optimize two-scale projection consistency between the generated …

Current object class recognition systems typically target 2D bounding box localization,
encouraged by benchmark data sets, such as Pascal VOC. While this seems suitable for the …

Geometric 3D reasoning at the level of objects has received renewed attention recently in
the context of visual scene understanding. The level of geometric detail, however, is typically …

As objects are inherently 3D, they have been modeled in 3D in the early days of computer
vision. Due to the ambiguities arising from map** 2D features to 3D models, 3D object …

Basic-level object category recognition has made remarkable progress over the last decade,
both in image-level categorization and bounding box localization settings [3]. More recently …