Search Results for author: Martin Rünz

Found 4 papers, 3 papers with code

DSP-SLAM: Object Oriented SLAM with Deep Shape Priors

1 code implementation21 Aug 2021 Jingwen Wang, Martin Rünz, Lourdes Agapito

We propose DSP-SLAM, an object-oriented SLAM system that builds a rich and accurate joint map of dense 3D models for foreground objects, and sparse landmark points to represent the background.

3D Object Reconstruction Object SLAM +1

FroDO: From Detections to 3D Objects

no code implementations11 May 2020 Kejie Li, Martin Rünz, Meng Tang, Lingni Ma, Chen Kong, Tanner Schmidt, Ian Reid, Lourdes Agapito, Julian Straub, Steven Lovegrove, Richard Newcombe

We introduce FroDO, a method for accurate 3D reconstruction of object instances from RGB video that infers object location, pose and shape in a coarse-to-fine manner.

3D Reconstruction Object Reconstruction +1

MaskFusion: Real-Time Recognition, Tracking and Reconstruction of Multiple Moving Objects

1 code implementation24 Apr 2018 Martin Rünz, Maud Buffier, Lourdes Agapito

We present MaskFusion, a real-time, object-aware, semantic and dynamic RGB-D SLAM system that goes beyond traditional systems which output a purely geometric map of a static scene.

Object Recognition Object SLAM +2

Co-Fusion: Real-time Segmentation, Tracking and Fusion of Multiple Objects

1 code implementation20 Jun 2017 Martin Rünz, Lourdes Agapito

In this paper we introduce Co-Fusion, a dense SLAM system that takes a live stream of RGB-D images as input and segments the scene into different objects (using either motion or semantic cues) while simultaneously tracking and reconstructing their 3D shape in real time.

Instance Segmentation Object SLAM +1

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