Recent years have witnessed enormous progress in AI-related fields such as computer
vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it …

Pedestrian detection is a key problem in computer vision, with several applications that have
the potential to positively impact quality of life. In recent years, the number of approaches to …

Current 3D object detection methods are heavily influenced by 2D detectors. In order to
leverage architectures in 2D detectors, they often convert 3D point clouds to regular grids …

Modern 3D semantic instance segmentation approaches predominantly rely on specialized
voting mechanisms followed by carefully designed geometric clustering techniques. Building …

Numerous deep learning applications benefit from multi-task learning with multiple
regression and classification objectives. In this paper we make the observation that the …

The ability to recognize, localize and track dynamic objects in a scene is fundamental to
many real-world applications, such as self-driving and robotic systems. Yet, traditional …

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 …

Abstract 3D instance segmentation, with a variety of applications in robotics and augmented
reality, is in large demands these days. Unlike 2D images that are projective observations of …

We address the problem of determining correspondences between two images in
agreement with a geometric model such as an affine or thin-plate spline transformation, and …

Cross-view geo-localization is to spot images of the same geographic target from different
platforms, eg, drone-view cameras and satellites. It is challenging in the large visual …