Search Results for author: Yuting Xu

Found 6 papers, 3 papers with code

Learning Spatiotemporal Inconsistency via Thumbnail Layout for Face Deepfake Detection

1 code implementation15 Mar 2024 Yuting Xu, Jian Liang, Lijun Sheng, Xiao-Yu Zhang

The deepfake threats to society and cybersecurity have provoked significant public apprehension, driving intensified efforts within the realm of deepfake video detection.

DeepFake Detection Face Swapping

TALL: Thumbnail Layout for Deepfake Video Detection

1 code implementation ICCV 2023 Yuting Xu, Jian Liang, Gengyun Jia, Ziming Yang, Yanhao Zhang, Ran He

This paper introduces a simple yet effective strategy named Thumbnail Layout (TALL), which transforms a video clip into a pre-defined layout to realize the preservation of spatial and temporal dependencies.

Face Swapping

mmWave RIS Phase Shift Feedback Based on Knowledge Base Autoencoder Framework

no code implementations27 Apr 2023 Hao Feng, Yuting Xu, Yuping Zhao

Then the knowledge base vectors index is obtained by calculating the similarity between feature vectors and knowledge base vectors and transmitted to the RIS.

Development and Evaluation of Conformal Prediction Methods for QSAR

no code implementations3 Apr 2023 Yuting Xu, Andy Liaw, Robert P. Sheridan, Vladimir Svetnik

The quantitative structure-activity relationship (QSAR) regression model is a commonly used technique for predicting biological activities of compounds using their molecular descriptors.

Conformal Prediction Prediction Intervals +1

Masked Relation Learning for DeepFake Detection

2 code implementations 2023 2023 Ziming Yang, Jian Liang, Yuting Xu, Xiao-Yu Zhang, Ran He

A relation learning module masks partial correlations between regions to reduce redundancy and then propagates the relational information across regions to capture the irregularity from a global view of the graph.

Binary Classification DeepFake Detection +3

Unsupervised Learning Discriminative MIG Detectors in Nonhomogeneous Clutter

no code implementations24 Apr 2022 Xiaoqiang Hua, Yusuke Ono, Linyu Peng, Yuting Xu

We define a projection that maps the HPD matrices in a high-dimensional manifold to a low-dimensional and more discriminative one to increase the degree of separation of HPD matrices by maximizing the data variance.

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