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20152022
most citedDeepFactors: Real-Time Probabilistic Dense Monocular SLAM

160 citations · 628 across the 19 of their papers we have counts for

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Showing 2021Show all

6 papers · 1 filter

cs.CV20211 cited

CodeMapping: Real-Time Dense Mapping for Sparse SLAM using Compact Scene Representations

Hidenobu Matsuki, Raluca Scona, Jan Czarnowski +1

We propose a novel dense mapping framework for sparse visual SLAM systems which leverages a compact scene representation. State-of-the-art sparse visual SLAM systems provide accura…

cs.AI202121 cited

A visual introduction to Gaussian Belief Propagation

Joseph Ortiz, Talfan Evans, Andrew J. Davison

In this article, we present a visual introduction to Gaussian Belief Propagation (GBP), an approximate probabilistic inference algorithm that operates by passing messages between t…

cs.CV2021

SIMstack: A Generative Shape and Instance Model for Unordered Object Stacks

Zoe Landgraf, Raluca Scona, Tristan Laidlow +3

By estimating 3D shape and instances from a single view, we can capture information about an environment quickly, without the need for comprehensive scanning and multi-view fusion.…

cs.CV2021

In-Place Scene Labelling and Understanding with Implicit Scene Representation

Shuaifeng Zhi, Tristan Laidlow, Stefan Leutenegger +1

Semantic labelling is highly correlated with geometry and radiance reconstruction, as scene entities with similar shape and appearance are more likely to come from similar classes.…

cs.CV2021

iMAP: Implicit Mapping and Positioning in Real-Time

Edgar Sucar, Shikun Liu, Joseph Ortiz +1

We show for the first time that a multilayer perceptron (MLP) can serve as the only scene representation in a real-time SLAM system for a handheld RGB-D camera. Our network is trai…

cs.RO20211 cited

End-to-End Egospheric Spatial Memory

Daniel Lenton, Stephen James, Ronald Clark +1

Spatial memory, or the ability to remember and recall specific locations and objects, is central to autonomous agents' ability to carry out tasks in real environments. However, mos…