no code implementations • 28 Sep 2023 • Pengfei Pei, Xianfeng Zhao, Jinchuan Li, Yun Cao
These features are widely present in different types of synthetic forgeries and help improve generalization for detecting unknown videos.
1 code implementation • 29 Jun 2023 • Haoqin Tu, Bowen Yang, Xianfeng Zhao
Automatically generating textual content with desired attributes is an ambitious task that people have pursued long.
1 code implementation • 15 Dec 2021 • Pengfei Pei, Xianfeng Zhao, Yun Cao, Jinchuan Li, Xuyuan Lai
In addition, we designed a tool called Localizator to compare the difference between the original traced video and the fake video.
1 code implementation • 18 Oct 2021 • Zhenyu Zhang, Yewei Gu, Xiaowei Yi, Xianfeng Zhao
As increasing development of text-to-speech (TTS) and voice conversion (VC) technologies, the detection of synthetic speech has been suffered dramatically.
2 code implementations • 6 Oct 2021 • Yewei Gu, Zhenyu Zhang, Xiaowei Yi, Xianfeng Zhao
To realize any-to-any (A2A) voice conversion (VC), most methods are to perform symmetric self-supervised reconstruction tasks (Xi to Xi), which usually results in inefficient performances due to inadequate feature decoupling, especially for unseen speakers.
no code implementations • 24 Jun 2021 • Wei Lu, Lingyi Liu, Junwei Luo, Xianfeng Zhao, Yicong Zhou, Jiwu Huang
And a spatial-temporal model is proposed which has two components for capturing spatial and temporal forgery traces in global perspective respectively.
1 code implementation • journal 2020 • Weike You, Hong Zhang, Xianfeng Zhao
On the assumption that natural image noise is similar between different image sub-regions, we propose an end-to-end, deep learning, novel solution for distinguishing steganography images from normal images that provides satisfying performance.
1 code implementation • 13 Nov 2019 • Zhongliang Yang, Ke Wang, Sai Ma, Yongfeng Huang, Xiangui Kang, Xianfeng Zhao
We hope that this test set can help to evaluate the robustness of steganalysis algorithms.
no code implementations • 8 Sep 2018 • Yaqi Liu, Xianfeng Zhao, Xiaobin Zhu, Yun Cao
Constrained image splicing detection and localization (CISDL) is a newly proposed challenging task for image forensics, which investigates two input suspected images and identifies whether one image has suspected regions pasted from the other.
no code implementations • 28 Aug 2017 • Ruxin Wang, Wei Lu, Shijun Xiang, Xianfeng Zhao, Jinwei Wang
In this paper, a color image splicing detection approach is proposed based on Markov transition probability of quaternion component separation in quaternion discrete cosine transform (QDCT) domain and quaternion wavelet transform (QWT) domain.
no code implementations • 5 Jul 2017 • Yaqi Liu, Qingxiao Guan, Xianfeng Zhao
Numerous experiments are conducted to demonstrate the effectiveness and robustness of the GPU version of Convolutional Kernel Network, and the state-of-the-art performance of the proposed copy-move forgery detection method based on Convolutional Kernel Network.
1 code implementation • 13 Jun 2017 • Yaqi Liu, Qingxiao Guan, Xianfeng Zhao, Yun Cao
In this paper, we propose to utilize Convolutional Neural Networks (CNNs) and the segmentation-based multi-scale analysis to locate tampered areas in digital images.