382 citations · 801 across the 48 of their papers we have counts for
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SA6D: Self-Adaptive Few-Shot 6D Pose Estimator for Novel and Occluded Objects
Ning Gao, Ngo Anh Vien, Hanna Ziesche +1
To enable meaningful robotic manipulation of objects in the real-world, 6D pose estimation is one of the critical aspects. Most existing approaches have difficulties to extend pred…
Enhancing Interpretable Object Abstraction via Clustering-based Slot Initialization
Ning Gao, Bernard Hohmann, Gerhard Neumann
Object-centric representations using slots have shown the advances towards efficient, flexible and interpretable abstraction from low-level perceptual features in a compositional s…
SyMFM6D: Symmetry-aware Multi-directional Fusion for Multi-View 6D Object Pose Estimation
Fabian Duffhauss, Sebastian Koch, Hanna Ziesche +2
Detecting objects and estimating their 6D poses is essential for automated systems to interact safely with the environment. Most 6D pose estimators, however, rely on a single camer…
FusionVAE: A Deep Hierarchical Variational Autoencoder for RGB Image Fusion
Fabian Duffhauss, Ngo Anh Vien, Hanna Ziesche +1
Sensor fusion can significantly improve the performance of many computer vision tasks. However, traditional fusion approaches are either not data-driven and cannot exploit prior kn…
MV6D: Multi-View 6D Pose Estimation on RGB-D Frames Using a Deep Point-wise Voting Network
Fabian Duffhauss, Tobias Demmler, Gerhard Neumann
Estimating 6D poses of objects is an essential computer vision task. However, most conventional approaches rely on camera data from a single perspective and therefore suffer from o…
Category-Agnostic 6D Pose Estimation with Conditional Neural Processes
Yumeng Li, Ning Gao, Hanna Ziesche +1
We present a novel meta-learning approach for 6D pose estimation on unknown objects. In contrast to ``instance-level" and ``category-level" pose estimation methods, our algorithm l…
What Matters For Meta-Learning Vision Regression Tasks?
Ning Gao, Hanna Ziesche, Ngo Anh Vien +2
Meta-learning is widely used in few-shot classification and function regression due to its ability to quickly adapt to unseen tasks. However, it has not yet been well explored on r…