Object detection can be regarded as one of the most fundamental and challenging visual
recognition task in computer vision and it has received great attention over the past few …

Object detection is one of the most important and challenging branches of computer vision,
which has been widely applied in people's life, such as monitoring security, autonomous …

Ordinal regression attempts to solve classification problems in which categories are not
independent, but rather follow a natural order. It is crucial to classify each class correctly …

In this paper, we present a novel probabilistic generative model for multi-object traffic scene
understanding from movable platforms which reasons jointly about the 3D scene layout as …

Hough transform-based methods for detecting multiple objects use nonmaxima suppression
or mode seeking to locate and distinguish peaks in Hough images. Such postprocessing …

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 …

We propose a novel method for detecting horizontal vanishing points and the zenith
vanishing point in man-made environments. The dominant trend in existing methods is to …

We address shape grammar parsing for facade segmentation using Reinforcement Learning
(RL). Shape parsing entails simultaneously optimizing the geometry and the topology (eg …

Deep learning has improved vanishing point detection in images. Yet, deep networks
require expensive annotated datasets trained on costly hardware and do not generalize to …

The objective of this paper is to rectify any monocular image by computing a homography
matrix that transforms it to a geometrically correct bird's eye (overhead) view. We make the …