frivolous
发表于 2025-3-25 03:44:07
Conditional Adversarial Camera Model Anonymizationl attribution classifier, which constrains the generative network to transform the full range of artifacts. Quantitative comparisons demonstrate the efficacy of our framework in a restrictive non-interactive black-box setting.
PHAG
发表于 2025-3-25 09:21:57
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PAD416
发表于 2025-3-25 12:16:26
https://doi.org/10.1007/978-3-7908-2078-2petition, and 5 teams (one withdrawn) have competed in the final testing phase. The winning team proposes the enhanced quadratic video interpolation method and achieves state-of-the-art on the VTSR task.
chapel
发表于 2025-3-25 17:56:45
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MILL
发表于 2025-3-25 21:08:04
The Latin American Studies Book Seriesthat, by fusing the dense connection mechanism and diversity enhancement devices, our proposed method achieves state-of-the-art accuracy and predicts sharp depth maps that restore reliable object structures.
Femine
发表于 2025-3-26 02:56:01
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伸展
发表于 2025-3-26 07:01:57
DeepGIN: Deep Generative Inpainting Network for Extreme Image Inpaintingng results. Our DeepGIN outperforms the state-of-the-art approaches generally, including two publicly available datasets (FFHQ and Oxford Buildings), both quantitatively and qualitatively. We also demonstrate that our model is capable of completing masked images in the wild.
insurgent
发表于 2025-3-26 10:45:33
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有常识
发表于 2025-3-26 13:29:12
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真实的人
发表于 2025-3-26 19:40:34
Densely Connecting Depth Maps for Monocular Depth Estimationthat, by fusing the dense connection mechanism and diversity enhancement devices, our proposed method achieves state-of-the-art accuracy and predicts sharp depth maps that restore reliable object structures.