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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: ergonomics
21#
發(fā)表于 2025-3-25 05:57:31 | 只看該作者
Genetik allergischer Erkrankungen,for this task is extremely expensive. As such, prior work has looked at unsupervised instance detection and segmentation, but in the absence of annotated boxes, it is unclear how pixels must be grouped into objects and which objects are of interest. This results in over-/under-segmentation and irrel
22#
發(fā)表于 2025-3-25 10:05:52 | 只看該作者
Giovanni Passalacqua,Giorgio Walter Canonicapromising, the quality factors that are considered in these works are general rather than FR-specific, .., atmospheric turbulence, resolution, .. Motivated by the observation of the vulnerability of current FR models to even small Face Alignment Errors (FAE) in LQ images, we present a simple yet eff
23#
發(fā)表于 2025-3-25 13:58:04 | 只看該作者
24#
發(fā)表于 2025-3-25 18:04:07 | 只看該作者
,OMR: Occlusion-Aware Memory-Based Refinement for?Video Lane Detection,, we apply a novel data augmentation scheme for training the OMR module effectively. Experimental results show that the proposed algorithm outperforms existing techniques on video lane datasets. Our codes are available at ..
25#
發(fā)表于 2025-3-25 23:45:28 | 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..
26#
發(fā)表于 2025-3-26 03:26:17 | 只看該作者
Conference proceedings 2025uter 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; reinforceme
27#
發(fā)表于 2025-3-26 07:30:32 | 只看該作者
Allergie und physikalische Faktoren, we apply a novel data augmentation scheme for training the OMR module effectively. Experimental results show that the proposed algorithm outperforms existing techniques on video lane datasets. Our codes are available at ..
28#
發(fā)表于 2025-3-26 10:53:08 | 只看該作者
Werner Heppt,Harald Renz,Martin R?ckenface non-rigidly while maintaining the consistency of the local shape. Experimental results demonstrate the significant superiority of DynoSurf over current state-of-the-art approaches, showcasing its potential as a powerful tool for dynamic mesh reconstruction. The code is publicly available at ..
29#
發(fā)表于 2025-3-26 13:31:47 | 只看該作者
30#
發(fā)表于 2025-3-26 20:28:06 | 只看該作者
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