Boosting Self-Supervision for Single View Scene Completion via Knowledge Distillation
kdbts is to boost single-view scene completion by exploiting additional information from multiple images.
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S4C: Self-Supervised Semantic Scene Completion with Neural Fields
S4C is the first self-supervised approach to the Sematic Scence Completion task. It achives close to state-of-the-art performance on the KITTI-360 SSCBench dataset.
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Learning Correspondence Uncertainty via Differentiable Nonlinear Least Squares
A differentiable nonlinear least squares framework to account for uncertainty in relative pose estimation from feature correspondences regardless of the feature extraction algorithm of choice.
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Probabilistic Normal Epipolar Constraint for Frame-To-Frame Rotation Optimization under Uncertain Feature Positions
We propose a probabilistic extension to the normal epipolar constraint (NEC) which we call the PNEC. It allows to account for keypoint position uncertainty in images to produce more accurate frame to frame pose estimates.
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