452 citations · 504 across the 14 of their papers we have counts for
12 papers · 1 filter
O-SCD++: Replay-Free Online Scene Change Detection via Recursive Evidence Fusion
Chamuditha Jayanga Galappaththige, Jason Lai, Lloyd Windrim +4
Online scene change detection requires an agent to detect what has changed in a previously mapped environment while it is still on site, observing from unconstrained viewpoints and…
From Pixels to Primitives: Scene Change Detection in 3D Gaussian Splatting
Chamuditha Jayanga Galappaththige, Jason Lai, Timothy Patten +3
Scene change detection methods built on Gaussian splatting universally follow a render-then-compare paradigm: the pre-change scene is rendered into 2D and compared against post-cha…
TrackAgent: 6D Object Tracking via Reinforcement Learning
Konstantin Röhrl, Dominik Bauer, Timothy Patten +1
Tracking an object's 6D pose, while either the object itself or the observing camera is moving, is important for many robotics and augmented reality applications. While exploiting…
COPE: End-to-end trainable Constant Runtime Object Pose Estimation
Stefan Thalhammer, Timothy Patten, Markus Vincze
State-of-the-art object pose estimation handles multiple instances in a test image by using multi-model formulations: detection as a first stage and then separately trained network…
SporeAgent: Reinforced Scene-level Plausibility for Object Pose Refinement
Dominik Bauer, Timothy Patten, Markus Vincze
Observational noise, inaccurate segmentation and ambiguity due to symmetry and occlusion lead to inaccurate object pose estimates. While depth- and RGB-based pose refinement approa…
ReAgent: Point Cloud Registration using Imitation and Reinforcement Learning
Dominik Bauer, Timothy Patten, Markus Vincze
Point cloud registration is a common step in many 3D computer vision tasks such as object pose estimation, where a 3D model is aligned to an observation. Classical registration met…
Sim2Real 3D Object Classification using Spherical Kernel Point Convolution and a Deep Center Voting Scheme
Jean-Baptiste Weibel, Timothy Patten, Markus Vincze
While object semantic understanding is essential for most service robotic tasks, 3D object classification is still an open problem. Learning from artificial 3D models alleviates th…
PyraPose: Feature Pyramids for Fast and Accurate Object Pose Estimation under Domain Shift
Stefan Thalhammer, Markus Leitner, Timothy Patten +1
Object pose estimation enables robots to understand and interact with their environments. Training with synthetic data is necessary in order to adapt to novel situations. Unfortuna…
Neural Object Learning for 6D Pose Estimation Using a Few Cluttered Images
Kiru Park, Timothy Patten, Markus Vincze
Recent methods for 6D pose estimation of objects assume either textured 3D models or real images that cover the entire range of target poses. However, it is difficult to obtain tex…
Addressing the Sim2Real Gap in Robotic 3D Object Classification
Jean-Baptiste Weibel, Timothy Patten, Markus Vincze
Object classification with 3D data is an essential component of any scene understanding method. It has gained significant interest in a variety of communities, most notably in robo…
VeREFINE: Integrating Object Pose Verification with Physics-guided Iterative Refinement
Dominik Bauer, Timothy Patten, Markus Vincze
Accurate and robust object pose estimation for robotics applications requires verification and refinement steps. In this work, we propose to integrate hypotheses verification with…
Pix2Pose: Pixel-Wise Coordinate Regression of Objects for 6D Pose Estimation
Kiru Park, Timothy Patten, Markus Vincze
Estimating the 6D pose of objects using only RGB images remains challenging because of problems such as occlusion and symmetries. It is also difficult to construct 3D models with p…