maroon 发表于 2025-4-1 03:48:29
uters. Traditional prior-based methods conduct favorable dehazing effect but tend to cause artifacts and color distortions due to inaccurate parameter estimations. By contrast, recent learning-based methods can provide better color fidelity via the supervised training of synthetic images. But unfort平静生活 发表于 2025-4-1 07:13:47
http://reply.papertrans.cn/103/10212/1021109/1021109_62.pnglavish 发表于 2025-4-1 13:14:31
http://reply.papertrans.cn/103/10212/1021109/1021109_63.pngMisgiving 发表于 2025-4-1 15:08:52
http://reply.papertrans.cn/103/10212/1021109/1021109_64.pngnonplus 发表于 2025-4-1 22:18:30
http://reply.papertrans.cn/103/10212/1021109/1021109_65.png刺耳的声音 发表于 2025-4-2 00:17:15
M. M. Caldwells), thereby eliminating expensive demands of mask annotation for new categories. Existing work mainly utilize the pipeline model of detection first and then segmentation, and explores how to provide more discriminative regions of interest for the class-agnostic mask head, but these methods do not peDENT 发表于 2025-4-2 06:11:53
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