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Deep Weighted Consensus: Dense correspondence confidence maps for 3D shape registration.

, and . CoRR, (2021)

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Multi-Velocity Neural Networks for Facial Expression Recognition in Videos., , and . IEEE Trans. Affect. Comput., 10 (2): 290-296 (2019)Deep Weighted Consensus: Dense correspondence confidence maps for 3D shape registration., and . CoRR, (2021)Dual Geometric Graph Network (DG2N) - Zero-Shot Refinement for Dense Shape Correspondence., and . CoRR, (2020)Unsupervised Volumetric Displacement Fields Using Cost Function Unrolling., and . MIDOG/MOOD/Learn2Reg@MICCAI, volume 13166 of Lecture Notes in Computer Science, page 153-160. Springer, (2021)Spectral Teacher for a Spatial Student: Spectrum-Aware Real-Time Dense Shape Correspondence., , and . 3DV, page 1-10. IEEE, (2022)Invariant metrics for non-rigid shapes.. Technion - Israel Institute of Technology, Israel, (2012)Learning Document Graphs with Attention for Image Manipulation Detection., , and . ICPRAI (1), volume 13363 of Lecture Notes in Computer Science, page 263-274. Springer, (2022)Shape-Consistent Generative Adversarial Networks for Multi-Modal Medical Segmentation Maps., , , and . ISBI, page 1-5. IEEE, (2022)Full and Partial Symmetries of Non-rigid Shapes., , , and . Int. J. Comput. Vis., 89 (1): 18-39 (2010)Occlusion Guided Self-supervised Scene Flow Estimation on 3D Point Clouds., and . 3DV, page 782-791. IEEE, (2021)