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Anonymized_COCO

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DataCite Commons2023-11-29 更新2025-04-16 收录
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https://ieee-dataport.org/documents/anonymizedcoco
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资源简介:
This dataset has been specially curated to demonstrate various image anonymization techniques for protecting privacy-sensitive areas. Gaussian blurring is used to selectively blur parts of the image, creating a blend of the original and blurred visuals. The pixelation process reduces the image to small pixel blocks and then resizes them back to their original dimensions, creating a pixelated appearance in designated areas. Distortion is implemented through elastic deformation, adding displacement fields generated by combining a Gaussian filter with a uniform random field to the image. Finally, the mask-out technique replaces critical privacy areas with a white mask, effectively erasing those parts of the image. These methods are particularly applied to the vehicle and person classes in the COCO dataset, underscoring their significance in the field of image-based privacy protection.   
提供机构:
IEEE DataPort
创建时间:
2023-11-29
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