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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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樓主: magnify
31#
發(fā)表于 2025-3-27 00:59:17 | 只看該作者
32#
發(fā)表于 2025-3-27 02:00:46 | 只看該作者
,SEA-RAFT: Simple, Efficient, Accurate RAFT for?Optical Flow,(1px), representing 22.9% and 17.8% error reduction from best published results. In addition, SEA-RAFT obtains the best cross-dataset generalization on KITTI and Spring. With its high efficiency, SEA-RAFT operates at least 2.3. faster than existing methods while maintaining competitive performance. The code is publicly available at ..
33#
發(fā)表于 2025-3-27 05:44:06 | 只看該作者
Conference proceedings 2025nt learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; motion estimation..
34#
發(fā)表于 2025-3-27 11:20:50 | 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
35#
發(fā)表于 2025-3-27 14:18:39 | 只看該作者
Allgemeine Betriebswirtschaftslehre(1px), representing 22.9% and 17.8% error reduction from best published results. In addition, SEA-RAFT obtains the best cross-dataset generalization on KITTI and Spring. With its high efficiency, SEA-RAFT operates at least 2.3. faster than existing methods while maintaining competitive performance. The code is publicly available at ..
36#
發(fā)表于 2025-3-27 18:29:40 | 只看該作者
37#
發(fā)表于 2025-3-27 23:34:17 | 只看該作者
38#
發(fā)表于 2025-3-28 05:04:14 | 只看該作者
Die Finanzwirtschaft der Unternehmung, recognizing the limitations of existing benchmarks in fully evaluating appearance awareness, we have constructed a synthetic dataset to rigorously validate our method. By effectively resolving the over-reliance on location information, we achieve state-of-the-art results on YouTube-VIS 2019/2021 an
39#
發(fā)表于 2025-3-28 07:19:41 | 只看該作者
40#
發(fā)表于 2025-3-28 10:54:23 | 只看該作者
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