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Titlebook: Computational Visual Media; 12th International C Fang-Lue Zhang,Andrei Sharf Conference proceedings 2024 The Editor(s) (if applicable) and

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樓主: 游牧
21#
發(fā)表于 2025-3-25 06:33:28 | 只看該作者
,6 Ar3H2S Hydrogen sulfide – argon (3/1),ency, we propose a voting method to select the un-occluded pixels to obtain the initial depth of the occluded point. We use a method to determine the specular region based on similar features of color and texture in the superpixel region and then present an optimization energy function to obtain the
22#
發(fā)表于 2025-3-25 10:12:19 | 只看該作者
23#
發(fā)表于 2025-3-25 13:20:14 | 只看該作者
https://doi.org/10.1007/978-3-540-47532-3ontent preservation and stylizing effects. Experiments and a user study confirm that our method substantially outperforms the state-of-the-art style transfer methods when both the style and content domain only contain one image each.
24#
發(fā)表于 2025-3-25 18:06:18 | 只看該作者
25#
發(fā)表于 2025-3-26 00:00:22 | 只看該作者
26#
發(fā)表于 2025-3-26 01:44:46 | 只看該作者
27#
發(fā)表于 2025-3-26 06:27:06 | 只看該作者
Explore and?Enhance the?Generalization of?Anomaly DeepFake Detectionegy (NRS) modules. BBMG leverages the inherent characteristics of boundary blur to simulate a comprehensive range of tampering techniques, enabling a more realistic representation of real-world scenarios. In conjunction with BBMG, the NRS module effectively mitigates the influence of noise samples.
28#
發(fā)表于 2025-3-26 09:03:03 | 只看該作者
29#
發(fā)表于 2025-3-26 13:18:47 | 只看該作者
Face Expression Recognition via?Product-Cross Dual Attention and?Neutral-Aware Anchor Loss, they do not consider the arousal degree of an expression. We propose a neutral-expression-aware expression feature similarity loss based on the traditional anchor loss, which can further guide the network to learn better features from an input image. Extensive experiments demonstrate the advantage
30#
發(fā)表于 2025-3-26 17:03:05 | 只看該作者
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