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Detection and Localization of Facial Expression Manipulations [article]

Ghazal Mazaheri, Amit K. Roy-Chowdhury
2021 arXiv   pre-print
To address this problem, we propose a framework that is able to detect manipulations in facial expression using a close combination of facial expression recognition and image manipulation methods.  ...  Concern regarding the wide-spread use of fraudulent images/videos in social media necessitates precise detection of such fraud.  ...  For this method a CNN is designed that uses the multi-task learning approach to simultaneously detect manipulated images and videos and locate the manipulated regions for each query.  ... 
arXiv:2103.08134v1 fatcat:hbhkuv6dibbgpnsor6mia5bepi

Robust Deepfake On Unrestricted Media: Generation And Detection [article]

Trung-Nghia Le and Huy H Nguyen and Junichi Yamagishi and Isao Echizen
2022 arXiv   pre-print
It also discusses possible ways to improve the robustness of deepfake detection for a wide variety of media (e.g., in-the-wild images and videos).  ...  This chapter explores the evolution of and challenges in deepfake generation and detection.  ...  Acknowledgments This research was partly supported by JSPS KAKENHI Grants (JP16H06302, JP18H04120, JP21H04907, JP20K23355, JP21K18023) and JST CREST Grants (JPMJCR20D3, JP-MJCR18A6), Japan.  ... 
arXiv:2202.06228v1 fatcat:a37q2lf7w5bcbekk5esmbx2goe

OpenForensics: Large-Scale Challenging Dataset For Multi-Face Forgery Detection And Segmentation In-The-Wild [article]

Trung-Nghia Le and Huy H. Nguyen and Junichi Yamagishi and Isao Echizen
2021 arXiv   pre-print
This paper presents a comprehensive study on two new countermeasure tasks: multi-face forgery detection and segmentation in-the-wild.  ...  We have also developed a suite of benchmarks for these tasks by conducting an extensive evaluation of state-of-the-art instance detection and segmentation methods on our newly constructed dataset in various  ...  This work was partially supported by JSPS KAKENHI Grants JP16H06302, JP18H04120, JP21H04907, JP20K23355, and JP21K18023, and by JST CREST Grants JPMJCR18A6 and JPMJCR20D3, including the AIP challenge program  ... 
arXiv:2107.14480v1 fatcat:2gj6bf2zz5dg5lvdcmu2ehiwe4

A Survey of Deep Facial Attribute Analysis [article]

Xin Zheng, Yanqing Guo, Huaibo Huang, Yi Li, Ran He
2019 arXiv   pre-print
Deep learning based facial attribute analysis consists of two basic sub-issues: facial attribute estimation (FAE), which recognizes whether facial attributes are present in given images, and facial attribute  ...  Additionally, we introduce the underlying theories of this two-stage pipeline for both FAE and FAM.  ...  [138] design a cascaded CNN for simultaneously learning face detection, facial landmark localization, and facial attribute estimation under a multi-task framework to improve the performance of each  ... 
arXiv:1812.10265v3 fatcat:tezgo2angvfefbttuoodnss6t4

A Survey of Deep Facial Attribute Analysis

Xin Zheng, Yanqing Guo, Huaibo Huang, Yi Li, Ran He
2020 International Journal of Computer Vision  
Deep learning based facial attribute analysis consists of two basic sub-issues: facial attribute estimation (FAE), which recognizes whether facial attributes are present in given images, and facial attribute  ...  Additionally, we introduce the underlying theories of this two-stage pipeline for both FAE and FAM.  ...  For example, considering the inherent dependencies of face-related tasks, design a cascaded CNN for simultaneously learning face detection, facial landmark localization, and facial attribute estimation  ... 
doi:10.1007/s11263-020-01308-z fatcat:xmlukvd5qbenzkzjacefhcnope

DFDT: An End-to-End DeepFake Detection Framework Using Vision Transformer

Aminollah Khormali, Jiann-Shiun Yuan
2022 Applied Sciences  
DFDT is specifically designed for deepfake detection tasks consisting of four main components: patch extraction & embedding, multi-stream transformer block, attention-based patch selection followed by  ...  Motivated by the aforementioned challenges, this work presents DFDT, an end-to-end deepfake detection framework that leverages the unique characteristics of transformer models, for learning hidden traces  ...  detection [23, 44] , and image segmentation [45] .  ... 
doi:10.3390/app12062953 fatcat:6vdlyruobjdpfnriivzj3xzzy4

M2TR: Multi-modal Multi-scale Transformers for Deepfake Detection [article]

Junke Wang, Zuxuan Wu, Wenhao Ouyang, Xintong Han, Jingjing Chen, Ser-Nam Lim, Yu-Gang Jiang
2022 arXiv   pre-print
In addition, to stimulate Deepfake detection research, we introduce a high-quality Deepfake dataset, SR-DF, which consists of 4,000 DeepFake videos generated by state-of-the-art face swapping and facial  ...  In particular, we introduce a Multi-modal Multi-scale TRansformer (M2TR), which operates on patches of different sizes to detect local inconsistencies in images at different spatial levels.  ...  manipulation clues and patch inconsistency separately, while [42] simultaneously identifies forged faces and locates the manipulated regions with multi-task learning.  ... 
arXiv:2104.09770v3 fatcat:hskipz7oxfcdrnix6b4rdgwnai

Not made for each other- Audio-Visual Dissonance-based Deepfake Detection and Localization [article]

Komal Chugh, Parul Gupta, Abhinav Dhall, Ramanathan Subramanian
2021 arXiv   pre-print
We also demonstrate temporal forgery localization, and show how our technique identifies the manipulated video segments.  ...  MDS is computed as an aggregate of dissimilarity scores between audio and visual segments in a video.  ...  A multi-task learning framework for fake detection-cumsegmentation of manipulated image (or video frame) regions is presented in [18] .  ... 
arXiv:2005.14405v3 fatcat:edlhq4i7njfuhf4w2noxykokl4

Detect and Locate: Exposing Face Manipulation by Semantic- and Noise-level Telltales [article]

Chenqi Kong, Baoliang Chen, Haoliang Li, Shiqi Wang, Anderson Rocha, Sam Kwong
2022 arXiv   pre-print
Generally speaking, detecting manipulated faces and locating the potentially altered regions are challenging tasks.  ...  The technological advancements of deep learning have enabled sophisticated face manipulation schemes, raising severe trust issues and security concerns in modern society.  ...  Following the experimental setting in [34] , we take 720 videos for training, 140 videos for validation, and 140 videos for testing.  ... 
arXiv:2107.05821v2 fatcat:tmnq75ggo5affdmmzxee3b6tgu

Attentive Semantic Exploring for Manipulated Face Detection [article]

Zehao Chen, Hua Yang
2020 arXiv   pre-print
Therefore, we propose a novel manipulated face detection method based on Multilevel Facial Semantic Segmentation and Cascade Attention Mechanism.  ...  However, due to the diversity of manipulation methods and the high quality of fake images, detection methods suffer from a lack of generalization ability.  ...  Re-use of Multi-scale Features For the five parts gotten from facial semantic segmentation, background and face are not resized.  ... 
arXiv:2005.02958v2 fatcat:4oejhyf54baszihexslaiz5ksy

VCIP 2020 Index

2020 2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)  
Adversarial Networks Han, Xiao A Dense-Gated U-Net for Brain Lesion Segmentation Han, Xiao Text-to-Image Generation via Semi-Supervised Training Han, Xiao Low Resolution Facial Manipulation  ...  Facial Manipulation Detection Wang, Xianglin Adaptive Color Transform in VVC Standard Wang, Xingtao A semantic labeling framework for ALS point clouds based on discretization and CNN Wang, Xiuheng  ... 
doi:10.1109/vcip49819.2020.9301896 fatcat:bdh7cuvstzgrbaztnahjdp5s5y

Intelligent Visual Media Processing: When Graphics Meets Vision

Ming-Ming Cheng, Qi-Bin Hou, Song-Hai Zhang, Paul L. Rosin
2017 Journal of Computer Science and Technology  
for 2D image understanding and 3D model analysis.  ...  processing tools, such as deep neural networks, provide effective ways for learning how to deal with heterogeneous visual data; iii) new data capture devices, such as the Kinect, bridge between algorithms  ...  Acknowledgments We would like to thank the anonymous reviewers for their useful feedback.  ... 
doi:10.1007/s11390-017-1681-7 fatcat:j6u7dzfbhfgnlpnluqajjbaxy4

VR content creation and exploration with deep learning: A survey

Miao Wang, Xu-Quan Lyu, Yi-Jun Li, Fang-Lue Zhang
2020 Computational Visual Media  
employed, designed specifically to handle panoramic images and video and virtual 3D scenes.  ...  VR content creation and exploration relates to image and video analysis, synthesis and editing, so deep learning methods such as fully convolutional networks and general adversarial networks are widely  ...  With a multi-task loss function and a fusion module, neutral 3D facial shape and expressive 3D facial shape are reconstructed.  ... 
doi:10.1007/s41095-020-0162-z fatcat:lgogzx26bvhn5f7uyefjkz7zny

An Overview of Face Manipulation Detection

Xingwang Ju
2020 Journal of Cyber Security  
Therefore, the detection of face manipulation becomes a critical issue in digital media forensics. This paper provides an overview of recent deep learning detection models for face manipulation.  ...  Some public dataset used for face manipulation detection is introduced. On this basis, the challenges for the research and the potential future directions are analyzed and discussed.  ...  In [35] , Nguyen et al. utilized the multi-task learning to locate the manipulated regions and detect whether is manipulated.  ... 
doi:10.32604/jcs.2020.014310 fatcat:fcu67ro5pvcg7eputna6dlf5eu

GIMP-ML: Python Plugins for using Computer Vision Models in GIMP [article]

Kritik Soman
2020 arXiv   pre-print
In addition, GIMP-ML also aims to bring the benefits of using deep learning networks used for computer vision tasks to routine image processing workflows.  ...  the use-cases for machine learning based image modification.  ...  It has been shown that several manual and time-consuming image processing tasks can be simplified by the use of deep learning models, which makes it convenient for the users of image manipulation software  ... 
arXiv:2004.13060v3 fatcat:sgyx2foitbds7k4v3bsc72qsjq
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