Zobrazeno 1 - 10
of 327
pro vyhledávání: '"LYU Siwei"'
Publikováno v:
Fushe yanjiu yu fushe gongyi xuebao, Vol 42, Iss 2, Pp 020401-020401 (2024)
Chimeras are universal phenomena in the M1-generation plants obtained following radiation-induced mutagenesis; however, the mutational effects and variant inheritance mechanisms of related rice chimeras have yet to be sufficiently clarified. In this
Externí odkaz:
https://doaj.org/article/263620122071416b9f0f3cddfc9df15c
The rapid growth of social media has resulted in an explosion of online news content, leading to a significant increase in the spread of misleading or false information. While machine learning techniques have been widely applied to detect fake news,
Externí odkaz:
http://arxiv.org/abs/2412.05843
Visual-textual inconsistency (VTI) evaluation plays a crucial role in cleansing vision-language data. Its main challenges stem from the high variety of image captioning datasets, where differences in content can create a range of inconsistencies (\eg
Externí odkaz:
http://arxiv.org/abs/2412.05685
This paper investigates the feasibility of a proactive DeepFake defense framework, {\em FacePosion}, to prevent individuals from becoming victims of DeepFake videos by sabotaging face detection. The motivation stems from the reliance of most DeepFake
Externí odkaz:
http://arxiv.org/abs/2412.01101
Meta-learning is a general approach to equip machine learning models with the ability to handle few-shot scenarios when dealing with many tasks. Most existing meta-learning methods work based on the assumption that all tasks are of equal importance.
Externí odkaz:
http://arxiv.org/abs/2410.18894
Detecting deepfakes has become an important task. Most existing detection methods provide only real/fake predictions without offering human-comprehensible explanations. Recent studies leveraging MLLMs for deepfake detection have shown improvements in
Externí odkaz:
http://arxiv.org/abs/2410.06126
Diffusion-based generative models have demonstrated their powerful performance across various tasks, but this comes at a cost of the slow sampling speed. To achieve both efficient and high-quality synthesis, various distillation-based accelerated sam
Externí odkaz:
http://arxiv.org/abs/2409.19681
Autor:
Zhan, Zheyuan, Chen, Defang, Mei, Jian-Ping, Zhao, Zhenghe, Chen, Jiawei, Chen, Chun, Lyu, Siwei, Wang, Can
Conditional image synthesis based on user-specified requirements is a key component in creating complex visual content. In recent years, diffusion-based generative modeling has become a highly effective way for conditional image synthesis, leading to
Externí odkaz:
http://arxiv.org/abs/2409.19365
In recent years, the multimedia forensics and security community has seen remarkable progress in multitask learning for DeepFake (i.e., face forgery) detection. The prevailing strategy has been to frame DeepFake detection as a binary classification p
Externí odkaz:
http://arxiv.org/abs/2408.16305
Recent research on knowledge distillation has increasingly focused on logit distillation because of its simplicity, effectiveness, and versatility in model compression. In this paper, we introduce Refined Logit Distillation (RLD) to address the limit
Externí odkaz:
http://arxiv.org/abs/2408.07703