Diff-PCR uses a diffusion model to learn denoising directions for refining doubly stochastic correspondence matrices, improving point cloud registration over one-shot normalization methods.
Pointpwc-net: A coarse-to-fine network for supervised and self-supervised scene flow estimation on 3d point clouds
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ESAM++ introduces a 3D Sparse Feature Pyramid Network for efficient online 3D scene perception on edge devices, claiming competitive accuracy with up to 3x faster inference and 2x smaller model size than ESAM on four benchmarks.
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Diff-PCR: Diffusion-Based Correspondence Searching in Doubly Stochastic Matrix Space for Point Cloud Registration
Diff-PCR uses a diffusion model to learn denoising directions for refining doubly stochastic correspondence matrices, improving point cloud registration over one-shot normalization methods.
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ESAM++: Efficient Online 3D Perception on the Edge
ESAM++ introduces a 3D Sparse Feature Pyramid Network for efficient online 3D scene perception on edge devices, claiming competitive accuracy with up to 3x faster inference and 2x smaller model size than ESAM on four benchmarks.