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LEGAU: Learning Semantic Gaussian Priors for Scalable Category-level Pose Estimation
Category-level 6D pose estimation from a single RGB-D observation is inherently under-constrained, since partial visible geometry must be interpreted together with a canonical object structure before a stable pose can be determined. We present LEGAU, a unified framework that jointly predicts NOCS co
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