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Found 7 papers, 3 papers with code
iPUNet:Iterative Cross Field Guided Point Cloud Upsampling
To solve the non-uniformity of input points, on top of the cross field guided upsampling, we further introduce an iterative strategy that refines the point distribution by moving sparse points onto the desired continuous 3D surface in each iteration.
3DTeethSeg'22: 3D Teeth Scan Segmentation and Labeling Challenge
To address these challenges, the 3DTeethSeg'22 challenge was organized in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) in 2022, with a call for algorithms tackling teeth localization, segmentation, and labeling from intraoral 3D scans.
Region-wise matching for image inpainting based on adaptive weighted low-rank decomposition
A non-convex weighted low-rank decomposition (NC-WLRD) model for LRMA is also proposed to reconstruct all degraded patch matrices grouped by the proposed RwM algorithm.
Dense Representative Tooth Landmark/axis Detection Network on 3D Model
Results show that our method can produce tooth landmarks with high accuracy.
Context-aware virtual adversarial training for anatomically-plausible segmentation
Despite their outstanding accuracy, semi-supervised segmentation methods based on deep neural networks can still yield predictions that are considered anatomically impossible by clinicians, for instance, containing holes or disconnected regions.
Self-paced and self-consistent co-training for semi-supervised image segmentation
Moreover, to encourage predictions from different networks to be both consistent and confident, we enhance this generalized JSD loss with an uncertainty regularizer based on entropy.
Texture Relative Superpixel Generation With Adaptive Parameters
Abstract—Superpixel generation, which is an essential step in many image processing applications, has attracted increasing attention from researchers.
