WebFoggy Cityscapes-refined is based on a refined list of 550 Cityscapes images (498 train plus 52 val) that yield high-quality synthetic foggy images; details are given in our … WebOct 24, 2024 · Domain adaptation provides a solution by adapting existing labels to the target testing data. However, a large gap between domains could make adaptation a challenging task, which leads to unstable training processes and sub-optimal results. In this paper, we propose to bridge the domain gap with an intermediate domain and …
Semantic Foggy Scene Understanding with Synthetic Data
Webfog_simulation-SFSU_synthetic/source/Demo_fog_simulation_Cityscapes.m Go to file Cannot retrieve contributors at this time 154 lines (119 sloc) 6.13 KB Raw Blame % Demo of fog simulation pipeline presented in our article % "Semantic Foggy Scene Understanding with Synthetic Data" % (International Journal of Computer Vision, 2024) WebAug 25, 2024 · We apply our fog synthesis on the Cityscapes dataset and generate Foggy Cityscapes with 20550 images. SFSU is tackled in two ways: 1) with typical supervised learning, and 2) with a novel type of semi-supervised learning, which combines 1) with an unsupervised supervision transfer from clear-weather images to their synthetic foggy … cherokee nation tag office tahlequah oklahoma
Foggy Cityscapes Dataset Papers With Code
WebApr 11, 2024 · The key difference between this (which I like) and what we see in a lot of contemporary superhero fare is that the design of the environment, while foggy and obscured, doesn’t feel *muddy*. The image is also super expressive, it isn’t just a smudgy concrete cityscape or whatever. 11 Apr 2024 16:51:36 WebJan 15, 2024 · The Cityscapes dataset was used as the source domain, while the Foggy Cityscape dataset was used as the target domain. In the experiments, the model was trained with the labeled images from Cityscapes and the unlabeled images from Foggy Cityscapes. We report the testing results on the validation set of Foggy Cityscapes. WebOct 9, 2024 · 为了实现在恶劣天气下的自动驾驶环境感知,大量工作通过人工合成雨、雾的方式来生成恶劣天气数据集。图像合成雾代码实现基于论文Semantic Foggy Scene Understanding with Synthetic Data(基于合成数据的语义雾景理解),它是在Cityscapes数据集的基础上进行合成,生成了Cityscapes_foggy数据集。 flights from norfolk to tokyo