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pro vyhledávání: '"Qu, Yiting"'
With the advent of text-to-image models and concerns about their misuse, developers are increasingly relying on image safety classifiers to moderate their generated unsafe images. Yet, the performance of current image safety classifiers remains unkno
Externí odkaz:
http://arxiv.org/abs/2405.03486
To prevent the mischievous use of synthetic (fake) point clouds produced by generative models, we pioneer the study of detecting point cloud authenticity and attributing them to their sources. We propose an attribution framework, FAKEPCD, to attribut
Externí odkaz:
http://arxiv.org/abs/2312.11213
State-of-the-art Text-to-Image models like Stable Diffusion and DALLE$\cdot$2 are revolutionizing how people generate visual content. At the same time, society has serious concerns about how adversaries can exploit such models to generate unsafe imag
Externí odkaz:
http://arxiv.org/abs/2305.13873
Text-to-Image generation models have revolutionized the artwork design process and enabled anyone to create high-quality images by entering text descriptions called prompts. Creating a high-quality prompt that consists of a subject and several modifi
Externí odkaz:
http://arxiv.org/abs/2302.09923
The dissemination of hateful memes online has adverse effects on social media platforms and the real world. Detecting hateful memes is challenging, one of the reasons being the evolutionary nature of memes; new hateful memes can emerge by fusing hate
Externí odkaz:
http://arxiv.org/abs/2212.06573
Publikováno v:
In Composites Part A February 2024 177
Akademický článek
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Publikováno v:
2013 IEEE International Geoscience & Remote Sensing Symposium - IGARSS; 2013, p3868-3871, 4p