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ViFu: Multiple 360$^\circ$ Objects Reconstruction with Clean Background via Visible Part Fusion
In this paper, we propose a method to segment and recover a static, clean background and multiple 360$^\circ$ objects from observations of scenes at different timestamps.
DiffusionNOCS: Managing Symmetry and Uncertainty in Sim2Real Multi-Modal Category-level Pose Estimation
This paper addresses the challenging problem of category-level pose estimation.
GS-Pose: Category-Level Object Pose Estimation via Geometric and Semantic Correspondence
This requires significantly less data to train than prior methods since the semantic features are robust to object texture and appearance.
A Probabilistic Rotation Representation for Symmetric Shapes With an Efficiently Computable Bingham Loss Function
In order to handle the ambiguity, the Bingham distribution is one promising solution.
Probabilistic Rotation Representation With an Efficiently Computable Bingham Loss Function and Its Application to Pose Estimation
In recent years, a deep learning framework has been widely used for object pose estimation.
Sim2Real Instance-Level Style Transfer for 6D Pose Estimation
This improves the quality of synthetic data for training pose estimation networks.
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