The field of image denoising is currently dominated by discriminative deep learning methods
that are trained on pairs of noisy input and clean target images. Recently it has been shown …

Deep Learning (DL) methods are powerful analytical tools for microscopy and can outperform
conventional image processing pipelines. Despite the enthusiasm and innovations fuelled …

This work addresses the problem of estimating the 6D Pose of specific objects from a single
RGB-D image. We present a flexible approach that can deal with generic objects, both …

RANSAC is an important algorithm in robust optimization and a central building block for
many computer vision applications. In recent years, traditionally hand-crafted pipelines have …

In recent years, the task of estimating the 6D pose of object instances and complete scenes,
ie camera localization, from a single input image has received considerable attention. …

Abstract Analysis-by-synthesis has been a successful approach for many tasks in computer
vision, such as 6D pose estimation of an object in an RGB-D image which is the topic of this …

Scanning probe microscopy (SPM) has revolutionized the fields of materials, nano-science,
chemistry, and biology, by enabling mapping of surface properties and surface manipulation …

Today, Convolutional Neural Networks (CNNs) are the leading method for image denoising.
They are traditionally trained on pairs of images, which are often hard to obtain for practical …

This paper addresses the task of estimating the 6D-pose of a known 3D object from a single
RGB-D image. Most modern approaches solve this task in three steps: i) compute local …

Cytoplasmic dynein is a motor protein that exerts force on microtubules. To generate force
for the movement of large organelles, dynein needs to be anchored, with the anchoring sites …