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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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41#
發(fā)表于 2025-3-28 17:45:28 | 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. The papers deal with topics such as computer vision; machine learning; deep neural netwo
42#
發(fā)表于 2025-3-28 19:44:14 | 只看該作者
43#
發(fā)表于 2025-3-29 01:27:40 | 只看該作者
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發(fā)表于 2025-3-29 03:39:00 | 只看該作者
45#
發(fā)表于 2025-3-29 07:28:51 | 只看該作者
46#
發(fā)表于 2025-3-29 13:29:52 | 只看該作者
,An Accurate Detection Is Not All You Need to?Combat Label Noise in?Web-Noisy Datasets,upon the recent empirical observation that applying unsupervised contrastive learning to noisy, web-crawled datasets yields a feature representation under which the in-distribution (ID) and out-of-distribution (OOD) samples are linearly separable [.]. We show that direct estimation of the separating
47#
發(fā)表于 2025-3-29 18:23:45 | 只看該作者
48#
發(fā)表于 2025-3-29 23:16:45 | 只看該作者
49#
發(fā)表于 2025-3-30 01:34:56 | 只看該作者
,Learned HDR Image Compression for?Perceptually Optimal Storage and?Display,er demand for superior image quality. As a result, HDR image compression is crucial to fully realize the benefits of HDR imaging without suffering from large file sizes and inefficient data handling. Conventionally, this is achieved by introducing a residual/gain map as additional metadata to bridge
50#
發(fā)表于 2025-3-30 05:02:06 | 只看該作者
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