3D object detection is a common function within the perception system of an autonomous
vehicle and outputs a list of 3D bounding boxes around objects of interest. Various 3D object …

We propose a structure-from-motion framework to recover accurate camera poses and point
clouds from unordered images. Traditional SfM systems typically rely on the successful …

The structure from motion (SfM) problem in computer vision is to recover the three-
dimensional (3D) structure of a stationary scene from a set of projective measurements …

We present an approach to indoor scene reconstruction from RGB-D video. The key idea is
to combine geometric registration of scene fragments with robust global optimization based …

Feature matching plays a crucial role in computer vision, with applications in visual
localization, simultaneous localization and map** (SLAM), image stitching, and more. It …

The Internet has become an unprecedented source of visual information about our world,
with millions of people uploading photos and videos to media-sharing sites at staggering …

Global structure-from-motion (SfM) methods solve all cameras simultaneously from all
available relative motions. It has better potential in both reconstruction accuracy and …

The problem of matching not just two, but m different sets of objects to each other arises in a
variety of contexts, including finding the correspondence between feature points across …

We present a linear method for global camera pose registration from pairwise relative poses
encoded in essential matrices. Our method minimizes an approximate geometric error to …

Depth estimation is a traditional computer vision task, which plays a crucial role in
understanding 3D scene geometry. Recently, algorithms that combine the multi-scale …