ReFlow6D predicts refractive flow and attenuation maps from an RGB image and uses them as intermediate features to regress the 6D pose of transparent objects, outperforming prior RGB-based methods on two benchmarks.
Handling object symmetries in cnn-based pose estimation,
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ReFlow6D: Refraction-Guided Transparent Object 6D Pose Estimation via Intermediate Representation Learning
ReFlow6D predicts refractive flow and attenuation maps from an RGB image and uses them as intermediate features to regress the 6D pose of transparent objects, outperforming prior RGB-based methods on two benchmarks.