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Titlebook: Computer Vision – ECCV 2024; 18th European Confer Ale? Leonardis,Elisa Ricci,Gül Varol Conference proceedings 2025 The Editor(s) (if applic

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21#
發(fā)表于 2025-3-25 06:56:48 | 只看該作者
https://doi.org/10.1007/978-3-322-82723-4uted from surface meshes and learned implicit fields from real multiview images. The experiment results show that our McGrids can significantly reduce the number of implicit field queries, resulting in significant memory reduction, while producing high-quality meshes with rich geometric details.
22#
發(fā)表于 2025-3-25 11:17:57 | 只看該作者
https://doi.org/10.1007/978-94-011-1946-7e core of ClusteringSDF, we introduce a highly efficient .?for lifting 2D labels to 3D. Experimental results on the challenging scenes from ScanNet and Replica datasets show that ClusteringSDF ?can achieve competitive performance compared to the state-of-the-art with significantly reduced training time.
23#
發(fā)表于 2025-3-25 12:57:29 | 只看該作者
Ortega Y Gasset, Phenomenology and Quixoted visually indicate them within images, outperforming strong baselines both on the binary alignment classification and the explanation generation tasks. Our code and human curated test set are available at: ..
24#
發(fā)表于 2025-3-25 16:02:03 | 只看該作者
,McGrids: Monte Carlo-Driven Adaptive Grids for?Iso-Surface Extraction,uted from surface meshes and learned implicit fields from real multiview images. The experiment results show that our McGrids can significantly reduce the number of implicit field queries, resulting in significant memory reduction, while producing high-quality meshes with rich geometric details.
25#
發(fā)表于 2025-3-25 21:28:15 | 只看該作者
,ClusteringSDF: Self-Organized Neural Implicit Surfaces for?3D Decomposition,e core of ClusteringSDF, we introduce a highly efficient .?for lifting 2D labels to 3D. Experimental results on the challenging scenes from ScanNet and Replica datasets show that ClusteringSDF ?can achieve competitive performance compared to the state-of-the-art with significantly reduced training time.
26#
發(fā)表于 2025-3-26 00:22:23 | 只看該作者
,Mismatch Quest: Visual and?Textual Feedback for?Image-Text Misalignment,d visually indicate them within images, outperforming strong baselines both on the binary alignment classification and the explanation generation tasks. Our code and human curated test set are available at: ..
27#
發(fā)表于 2025-3-26 04:20:06 | 只看該作者
28#
發(fā)表于 2025-3-26 12:23:05 | 只看該作者
29#
發(fā)表于 2025-3-26 14:57:56 | 只看該作者
30#
發(fā)表于 2025-3-26 16:48:54 | 只看該作者
0302-9743 ce on Computer Vision, ECCV 2024, held in Milan, Italy, during September 29–October 4, 2024...The 2387 papers presented in these proceedings were carefully reviewed and selected from a total of 8585 submissions. They deal with topics such as computer vision; machine learning; deep neural networks; r
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