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Found 5 papers, 0 papers with code
S2P3: Self-Supervised Polarimetric Pose Prediction
The novel training paradigm comprises 1) a physical model to extract geometric information of polarized light, 2) a teacher-student knowledge distillation scheme and 3) a self-supervised loss formulation through differentiable rendering and an invertible physical constraint.
DiffCAD: Weakly-Supervised Probabilistic CAD Model Retrieval and Alignment from an RGB Image
We formulate this as a conditional generative task, leveraging diffusion to learn implicit probabilistic models capturing the shape, pose, and scale of CAD objects in an image.
Polarimetric Information for Multi-Modal 6D Pose Estimation of Photometrically Challenging Objects with Limited Data
6D pose estimation pipelines that rely on RGB-only or RGB-D data show limitations for photometrically challenging objects with e. g. textureless surfaces, reflections or transparency.
Attention meets Geometry: Geometry Guided Spatial-Temporal Attention for Consistent Self-Supervised Monocular Depth Estimation
A novel temporal attention mechanism further processes the local geometric information in a global context across consecutive images.
