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Seeing Beyond Appearance - Mapping Real Images into Geometrical Domains for Unsupervised CAD-based Recognition., , , , , and . IROS, page 2579-2586. IEEE, (2019)3D Local Features for Direct Pairwise Registration., , and . CVPR, page 3244-3253. Computer Vision Foundation / IEEE, (2019)PPFNet: Global Context Aware Local Features for Robust 3D Point Matching., , and . CVPR, page 195-205. Computer Vision Foundation / IEEE Computer Society, (2018)SobolevFusion: 3D Reconstruction of Scenes Undergoing Free Non-Rigid Motion., , and . CVPR, page 2646-2655. Computer Vision Foundation / IEEE Computer Society, (2018)What Can We Learn About a Generated Image Corrupting Its Latent Representation?, , , , and . MICCAI (6), volume 13436 of Lecture Notes in Computer Science, page 505-515. Springer, (2022)NeRF-Pose: A First-Reconstruct-Then-Regress Approach for Weakly-supervised 6D Object Pose Estimation., , , , , , and . ICCV (Workshops), page 2115-2125. IEEE, (2023)MatchU: Matching Unseen Objects for 6D Pose Estimation from RGB-D Images., , , , , and . CoRR, (2024)Random ferns for multiple target tracking in microscopic retina image sequences., , , , , , , and . ISBI, page 209-212. IEEE, (2015)WeLSA: Learning to Predict 6D Pose from Weakly Labeled Data Using Shape Alignment., , , , and . ECCV (8), volume 13668 of Lecture Notes in Computer Science, page 645-661. Springer, (2022)An Octree-Based Approach towards Efficient Variational Range Data Fusion., , , , and . BMVC, BMVA Press, (2016)