Image Matching is a core component of all best-performing algorithms and pipelines in 3D
vision. Yet despite matching being fundamentally a 3D problem, intrinsically linked to …

As computer vision algorithms increase in capability, their applications in clinical systems
will become more pervasive. These applications include: diagnostics, such as colonoscopy …

Multi-view stereo reconstruction (MVS) in the wild requires to first estimate the camera
intrinsic and extrinsic parameters. These are usually tedious and cumbersome to obtain yet …

Recently, 6DoF object pose estimation has become increasingly important for a broad range
of applications in the fields of virtual reality, augmented reality, autonomous driving, and …

Abstract Recent work in Visual Odometry and SLAM has shown the effectiveness of using
deep network backbones. Despite excellent accuracy, such approaches are often expensive …

We address the task of estimating camera parameters from a set of images depicting a
scene. Popular feature-based structure-from-motion (SfM) tools solve this task by …

This paper introduces a novel framework for virtual try-on, termed Wear-Any-Way. Different
from previous methods, Wear-Any-Way is a customizable solution. Besides generating high …

Semantic 2D maps are commonly used by humans and machines for navigation purposes,
whether it's walking or driving. However, these maps have limitations: they lack detail, often …

Recent approaches to point tracking are able to recover the trajectory of any scene point
through a large portion of a video despite the presence of occlusions. They are however too …

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 …