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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Computer Vision – ECCV 2024978-3-031-72998-0Series ISSN 0302-9743 Series E-ISSN 1611-3349

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978-3-031-72997-3The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl

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https://doi.org/10.1007/978-1-349-07005-3ase. It is demonstrated with experiments that BDIA-DDIM is effective for (round-trip) prompt-driven image editing. Our experiments further show that BDIA-DDIM produces markedly better image sampling quality than DDIM and EDICT for text-to-image generation and conventional image sampling. BDIA can al

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Die Information beherrschen und teilenregions and spending most on the former, and ii) Object-Centric Token Merging, which reduces cost of cross-frame attention by fusing redundant tokens in unimportant background regions. Both techniques are readily applicable to a given video editing model . retraining, and can drastically reduce its

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