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Found 4 papers, 1 papers with code
Improving 2D-3D Dense Correspondences with Diffusion Models for 6D Object Pose Estimation
In this study, we compare image-to-image translation networks based on GANs and diffusion models for the downstream task of 6D object pose estimation.
STAR: Shape-focused Texture Agnostic Representations for Improved Object Detection and 6D Pose Estimation
To achieve a focus on learning shape features, the textures are randomized during the rendering of the training data.
Challenges for Monocular 6D Object Pose Estimation in Robotics
Object pose estimation is a core perception task that enables, for example, object grasping and scene understanding.
Open Challenges for Monocular Single-shot 6D Object Pose Estimation
Object pose estimation is a non-trivial task that enables robotic manipulation, bin picking, augmented reality, and scene understanding, to name a few use cases.
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