12 citations · 15 across the 6 of their papers we have counts for
5 papers · 1 filter
Feature-Realistic Neural Fusion for Real-Time, Open Set Scene Understanding
Kirill Mazur, Edgar Sucar, Andrew J. Davison
General scene understanding for robotics requires flexible semantic representation, so that novel objects and structures which may not have been known at training time can be ident…
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…
MoreFusion: Multi-object Reasoning for 6D Pose Estimation from Volumetric Fusion
Kentaro Wada, Edgar Sucar, Stephen James +2
Robots and other smart devices need efficient object-based scene representations from their on-board vision systems to reason about contact, physics and occlusion. Recognized preci…
NodeSLAM: Neural Object Descriptors for Multi-View Shape Reconstruction
Edgar Sucar, Kentaro Wada, Andrew Davison
The choice of scene representation is crucial in both the shape inference algorithms it requires and the smart applications it enables. We present efficient and optimisable multi-c…
Probabilistic Global Scale Estimation for MonoSLAM Based on Generic Object Detection
Edgar Sucar, Jean-Bernard Hayet
This paper proposes a novel method to estimate the global scale of a 3D reconstructed model within a Kalman filtering-based monocular SLAM algorithm. Our Bayesian framework integra…