Surgeon
发表于 2025-3-23 10:43:11
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Flounder
发表于 2025-3-23 14:02:20
Taking Sides: Hegel or Spinoza?tilizing a limited number of labeled samples in conjunction with an abundance of unlabeled data from the target domain. Simple aggregation of domain adaptation (DA) and semi-supervised learning (SSL) falls short of optimal performance due to two primary challenges: (1) skewed training data distribut
slow-wave-sleep
发表于 2025-3-23 18:00:44
https://doi.org/10.1007/978-3-642-78709-6 3D counterpart has received less attention, in part due to the scarcity of annotated 3D datasets, which are expensive to collect. In this work, we propose to leverage a few annotated 3D shapes or richly annotated 2D datasets to perform 3D object part segmentation. We present our novel approach, ter
神化怪物
发表于 2025-3-24 01:14:09
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happiness
发表于 2025-3-24 03:04:53
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助记
发表于 2025-3-24 07:03:08
https://doi.org/10.1007/978-981-13-1053-9ities between examples and the target. The resulting models can be generalized seamlessly to novel segmentation tasks, significantly reducing the labeling and training costs compared with conventional pipelines. However, in-context segmentation is more challenging than classic ones requiring the mod
在前面
发表于 2025-3-24 13:28:15
Juan Gorraiz,Benedikt Blahous,Martin Wieland Neural rendering methods based on point clouds do exist, but they do not perform well when the point cloud is sparse or incomplete, which is often the case with real-world data. We overcome these problems with a simple representation that aggregates point clouds at multiple scale levels with sparse
坦白
发表于 2025-3-24 15:47:44
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直觉好
发表于 2025-3-24 20:35:16
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菊花
发表于 2025-3-25 01:48:14
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