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Titlebook: Computer Vision – ECCV 2022; 17th European Confer Shai Avidan,Gabriel Brostow,Tal Hassner Conference proceedings 2022 The Editor(s) (if app

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樓主: CILIA
41#
發(fā)表于 2025-3-28 17:56:25 | 只看該作者
,Long Video Generation with?Time-Agnostic VQGAN and?Time-Sensitive Transformer, Sky Time-lapse, and Taichi-HD datasets can generate diverse, coherent, and high-quality long videos. We also showcase conditional extensions of our approach for generating meaningful long videos by incorporating temporal information with text and audio. Videos and code can be found at ..
42#
發(fā)表于 2025-3-28 20:18:26 | 只看該作者
43#
發(fā)表于 2025-3-29 00:35:01 | 只看該作者
,Editing Out-of-Domain GAN Inversion via?Differential Activations,construction cannot be faithful to the original input. The main reason for this is that the distributions between training and real-world data are misaligned, and because of that, it is unstable of GAN inversion for real image editing. In this paper, we propose a novel GAN prior based editing framew
44#
發(fā)表于 2025-3-29 05:44:42 | 只看該作者
45#
發(fā)表于 2025-3-29 07:14:33 | 只看該作者
46#
發(fā)表于 2025-3-29 12:55:49 | 只看該作者
,Inpainting at?Modern Camera Resolution by?Guided PatchMatch with?Auto-curation,ern cameras such as 4K or more, and for large holes. We contribute an inpainting benchmark dataset of photos at 4K and above representative of modern sensors. We demonstrate a novel framework that combines deep learning and traditional methods. We use an existing deep inpainting model LaMa?[.] to fi
47#
發(fā)表于 2025-3-29 17:47:53 | 只看該作者
48#
發(fā)表于 2025-3-29 22:47:48 | 只看該作者
49#
發(fā)表于 2025-3-30 00:52:24 | 只看該作者
50#
發(fā)表于 2025-3-30 06:23:02 | 只看該作者
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