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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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61#
發(fā)表于 2025-4-1 04:20:07 | 只看該作者
,Learning to?Enhance Aperture Phasor Field for?Non-Line-of-Sight Imaging,nals are detected. The phasor wavefronts at the aperture, which are band-limited signals, are employed as inputs and outputs of the network, guiding our network to learn from the frequency range of interests and discard unnecessary information. The experimental results in more practical acquisition
62#
發(fā)表于 2025-4-1 07:00:54 | 只看該作者
63#
發(fā)表于 2025-4-1 13:36:35 | 只看該作者
,Fine-Grained Dynamic Network for?Generic Event Boundary Detection,Besides, a multi-order difference detector is also proposed to ensure generic boundaries can be effectively identified and adaptively processed. Extensive experiments on the challenging Kinetics-GEBD and TAPOS datasets demonstrate that adopting the dynamic strategy significantly benefits GEBD tasks,
64#
發(fā)表于 2025-4-1 17:12:47 | 只看該作者
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發(fā)表于 2025-4-1 21:55:19 | 只看該作者
,AlignZeg: Mitigating Objective Misalignment for?Zero-Shot Semantic Segmentation,allocate a more generalizable feature space. . During the inference stage, AlignZeg uses a class indicator to find potential unseen class proposals followed by a prediction postprocess to correct the prediction bias. Experiments demonstrate that AlignZeg markedly enhances zero-shot semantic segmenta
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