activity
20182021
most citedA novel joint points and silhouette-based method to estimate 3D human pose and shape

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV2021

Generic Merging of Structure from Motion Maps with a Low Memory Footprint

Gabrielle Flood, David Gillsjö, Patrik Persson +2

With the development of cheap image sensors, the amount of available image data have increased enormously, and the possibility of using crowdsourced collection methods has emerged.…

cs.CV2020

Detailed 3D Human Body Reconstruction from Multi-view Images Combining Voxel Super-Resolution and Learned Implicit Representation

Zhongguo Li, Magnus Oskarsson, Anders Heyden

The task of reconstructing detailed 3D human body models from images is interesting but challenging in computer vision due to the high freedom of human bodies. In order to tackle t…

cs.CV20201 cited

A novel joint points and silhouette-based method to estimate 3D human pose and shape

Zhongguo Li, Anders Heyden, Magnus Oskarsson

This paper presents a novel method for 3D human pose and shape estimation from images with sparse views, using joint points and silhouettes, based on a parametric model. Firstly, t…

cs.CV2020

Efficient Real-Time Radial Distortion Correction for UAVs

Marcus Valtonen Örnhag, Patrik Persson, Mårten Wadenbäck +2

In this paper we present a novel algorithm for onboard radial distortion correction for unmanned aerial vehicles (UAVs) equipped with an inertial measurement unit (IMU), that runs…

cs.CV2018

Bilinear Parameterization For Differentiable Rank-Regularization

Marcus Valtonen Örnhag, Carl Olsson, Anders Heyden

Low rank approximation is a commonly occurring problem in many computer vision and machine learning applications. There are two common ways of optimizing the resulting models. Eith…