Deepfake research paper. [17] gives an in-depth analysis of visual deepfake creation techniques, however, deepfake detection approaches are only briefly discussed. We aim to broaden the state-of-the-art research by systematically reviewing the differ-ent categories of fake content detection. Feb 13, 2023 · Currently, no rule of procedure, ethics, or legal precedent directly addresses the presentation of the “deepfake defense” in court. Application of neural networks and deep learning is one approach. This paper generates fake audio | Find, read and cite all the research you Jun 10, 2021 · Deepfake technology is a relatively recent phenomenon. Explainability and interpretability of deepfake models. This paper provides a comprehensive review and detailed analysis of existing tools and machine learning (ML) based approaches for deepfake generation and the methodologies used to detect such manipulations for both audio and visual deepfakes. Deep fake images generated using PGGAN[17] General block diagram of Generative Adversarial Network (GAN) Apr 9, 2021 · Recently, deepfake videos, generated by deep learning algorithms, have attracted widespread attention. In fact, Deeptrace’s Ajder explained, a lot of deepfake content is labeled as a deepfake, because creators are trying to show off their work. They classified them into four categories: DL-based approaches, traditional ML-based techniques, statistical techniques, and Mar 13, 2024 · A deepfake 360°-deepfake was not evaluated as significantly more credible than the deepfake video (b = −0. In this paper, we explore a 2-phase learning architecture using Siamese Neural Networks [2] with CNNs for DeepFake detection. Mittal et al. Jan 1, 2020 · To fill this gap, in this paper, we provide a comprehensive overview and detailed analysis of the research work on the topic of DeepFake generation, DeepFake detection as well as evasion of DeepFake detection, with more than 318 research papers carefully surveyed. Adversarial watermark for combating deepfake. Sep 25, 2019 · This paper presents a survey of algorithms used to create deepfakes and, more importantly, methods proposed to detect deepfakes in the literature to date. This study leverages many papers on artificial intelligence techniques to address deepfake detection. The wider academic community learned about deepfakes in 2016 when Justus Thies and his colleagues presented their research on real-time face capture and re-enactment at the Conference on Computer Vision and Pattern Recognition (Thies et al. Applications of deepfake detection and prevention in real-world scenarios. Mar 18, 2024 · Deepfake refers to an artificial intelligence-based technique to produce manipulated videos that look realistic. Initially easy to detect, rapid advancements in Oct 25, 2023 · Technology known as deepfake (DT) has reached an entirely new level of complexity. However, its advancements have also led to concerns over privacy, democracy, and national security, particularly with the advent of deepfake technology. Jul 23, 2022 · In the last few years, with the advancement of deep learning methods, especially Generative Adversarial Networks (GANs) and Variational Auto-encoders (VAEs), fabricated content has become more realistic and believable to the naked eye. 913) and deepfake audio (b = 0. Dataset Number of real videos Number of Deepfake Apr 1, 2020 · This paper introduces a Convolutional Neural Network (CNN) based DL model specifically developed for the classification of Deepfake video frames. ZaoApp is a face-swapping app that uses clips from a great variety of films and TV shows, convincingly changing Exposing DeepFake Videos By Detecting Face Warping Artifacts. This Deepfake forensics and countermeasures. For example, Meta and Google have created large public deepfake datasets to advance research on deepfake detection, which were used in several of the computational studies quoted above in the “detection” section. It provides the necessary tools as well as an easy-to-use way to conduct high Jul 2, 2023 · This paper provides a review of the existing generation and detection methods of the various deepfake contents. This paper presents a survey of algorithms used to create deepfakes and, more importantly, methods proposed to detect deepfakes in the literature to date. In turn, video was not evaluated as more credible than the deepfake audio (b = 0. Dataset creation and benchmarking for deepfake analysis. Deepfakes are created by using machine learning algorithms to manipulate or replace parts of an original video or image, such as the face of a person. SB collected numerous examples and contributed substantial editing work. In this Mar 23, 2022 · A number of AI-generated tools are used today to clone human voices, leading to a new technology known as Audio Deepfakes (ADs). 70) (Supplemental Table A7). This paper also provides detailed information on available benchmark datasets in DeepFake detection research. In the paper, we make a survey Oct 1, 2022 · Although the obtained numbers of deepfake papers may be lower than actual numbers but the research trend of this topic is obviously increasing. This paper proposes a temporal-aware pipeline Aug 18, 2023 · Our secondary research questions, which leverage the contextual questions in the surveys to uncover drivers of vulnerabilities and potential avenues for deepfake mitigation, were as follows: 2. Nov 20, 2023 · Rana et al. This paper provides readers with a comprehensive and easy-to-understand state-of-the-art related to deepfake generation and detection. technology and get around new detection systems (CNN06). In a deepfake video, a person’s face, emotion or speech are replaced by someone else’s face, different emotion or speech, using deep learning technology. Deep fakes are altered, high-quality, realistic videos/images that have lately gained popularity. In this paper, we consider the deepfake detection technologies Xception and MobileNet as two approaches for classification tasks to automatically detect deepfake Feb 19, 2024 · The purpose of Mirsky and Lee is to provide a deeper understanding of deepfake creation and detection, identify the shortcomings of current defense solutions, and highlight areas requiring further research. This paper presents a comprehensive review of recent studies for deepfake content detection using deep learning-based approaches. Most of them model deepfake detection as a vanilla binary classification problem, i. They can have a heavy social, political and Feb 1, 2021 · So in this paper, we review various methods to detect deepfake images generated by GANs. This paper suggested a deep convolution GAN detection model as a solution to the challenge. The four main types of manipulation are identity swap, face reenactment, attribute manipulation, and entire face synthesis, where every category manipulation generation and such manipulation Feb 15, 2022 · manipulations. That’s why a lot of research and applications are being developed in both the deepfake generation as well as detection May 6, 2023 · This paper utilizes different machine learning methods to dete ct deepfake images. e, first use a backbone network to extract a global feature and then feed it of 2020, about 737 DeepFake related papers were expected. KP investigated and formulated the research trends in deepfake technology. May 4, 2022 · Moreover, at the end of this article, the potential research directions and challenges of Deepfake detection methods are discussed to discover that, even though AD detection is an active area of Jun 1, 2022 · In this paper, an approach for Deepfake detection has been provided. 9 These This section of the paper discusses methods, frameworks, models, and techniques for deepfake generation, technologies that can be used to create manipulated content, face swaps, lip sync, face reenactment, attribute manipulation, generative adversarial neural networks, and the forensic study of deepfakes. We first unify task definitions, comprehensively introduce datasets and metrics, and discuss developing technologies. Conclusion This paper proposed a metric of comparisons for various deep learning approaches that detect deep fake audio and for the implementation the model architectures were taken from papers by Malik et al [22], Wu et al [23], Chugh et al [24], Thai et al [25], and Reimao et al [26]. Fake images and videos including facial information generated by digital manipulation, in particular with DeepFake methods [1], have become a great public concern recently [2], [3]. 3 Research Design, Data, and Method Nov 7, 2022 · Hence, this review paper aims to i. Nov 1, 2020 · PDF | On Nov 1, 2020, Tianxiang Chen and others published Generalization of Audio Deepfake Detection | Find, read and cite all the research you need on ResearchGate Jun 16, 2022 · The first and foremost step in conducting a review is searching and selecting the most appropriate research papers. Nov 20, 2022 · The mushroomed Deepfake synthetic materials circulated on the internet have raised serious social impact to politicians, celebrities, and every human being on earth. This paper constrains the problem to binary image classification, with an image as the model input and a prediction of whether the image is real or fake as the output. Current DeepFake detectors show good classification re- May 12, 2020 · Deepfake defense not only requires the research of detection but also requires the efforts of generation methods. 2 Related work Sep 20, 2023 · To compile a comprehensive collection of research papers on DeepFakes from various study areas, we initially gathered the articles from a Github repository that contains more than 100 papers on DeepFakes generation and detection. Aug 24, 2023 · There are growing implications surrounding generative AI in the speech domain that enable voice cloning and real-time voice conversion from one individual to another. The majority of Jan 2, 2021 · In this article, we explore the creation and detection of deepfakes and provide an in-depth view as to how these architectures work. According to the best of our knowledge, this paper is the first attempt to provide a detailed analysis and review of both the audio This paper summarizes the current research situation of combating deepfake technology based on blockchain technology from three aspects of building a trusted network, tracing deepfake and content Tamper resistance prevention, analyzes the limitations and risks of using blockchain technology against deepfake technology, and discusses the future various available datasets, including FaceForensic++[1], Deepfake Detection Challenge[2], and Celeb-DF[3]. However, current deepfake methods suffer the effects of obscure workflow and poor performance. Introduction. There have been existing survey papers about creating and detecting deepfakes, presented in Tolosana et al. Cybercriminals now have the ability to modify sounds, images, and videos in order to mislead individuals and Aug 2, 2024 · Big data analytics, computer vision, and human-level governance are key areas where deep learning has been impactful. RTDFs can clone a target's voice in real-time over phone calls, making these interactions highly interactive and thus far more convincing. Nonetheless, the study reveals a notable Western-centric cultural inclination in the digital platforms and media samples analyzed, which may pose issues in extrapolating the findings to Jan 1, 2023 · 5. Since then, these Apr 23, 2024 · This research paper focuses on detecting and curbing the circulation of deepfake videos across social media platforms to prevent misuse. Similarly, there are no significant differences between the Jul 21, 2020 · But if you want to see a deepfake yourself, they’re not hard to find. Oct 1, 2022 · Catching the deepfake alarming problem, research community has focused on developing deepfake detection algorithms and numerous results have been reported. Many academics have expressed fears that deepfakes present a severe threat to the veracity of news and political communication, and an epistemic crisis for video evidence. The development of convincing fake content threatens politics, security, and privacy. 01, p = . Introduction On 29 September 2019, ZaoApp was introduced in China via iOS Store. 05, p = . We find that, to date, deepfake research is driven by computer science Feb 28, 2024 · Scammers are aggressively leveraging AI voice-cloning technology for social engineering attacks, a situation significantly worsened by the advent of audio Real-time Deepfakes (RTDFs). The Russo Apr 23, 2020 · Generative deep learning algorithms have progressed to a point where it is difficult to tell the difference between what is real and what is fake. , fake im- age detection and face video detection. There were detailed explanations of the methods used in Sep 26, 2019 · Categories of reviewed papers relevant to deepfake detection methods where we divide papers into two major groups, i. It is noticeable that a battle between those who use advanced machine Jun 15, 2023 · Deepfake technology can be used to forge synthetic media that people cannot differentiate from true ones. For example, researchers found that early [57], we refer to it in this paper AI-generated Oct 26, 2021 · The field research for Deepfake social impact research is emerging and this paper brings more insights drawn from a methodical, subject focused and distribution point of view. Oct 25, 2023 · Deepfakes are a form of multi-modal media generated using deep-learning technology. Nov 13, 2020 · The intent of this research paper is to understand the impact deepfakes make in society and to discuss the legal provisions against these activities and spreading awareness regarding the sharing The results from experiment 2, although statistically significant by conventional standards, were near the cutoff for statistical significance for authentic videos and not statistically significant for deepfake videos. Deeptrace was founded in late 2018 to provide capabilities (like software-as-a-service) for detecting deepfake images and videos. ResNext, a Convolutional Neural Network (CNN) algorithm and Long Short-Term Memory (LSTM) is used as an approach to detect the Deepfake videos. outline potential opportunities, research trends of deepfake in terms of Jan 1, 2020 · Under the aegis of computer vision and deep learning technology, a new emerging techniques has introduced that anyone can make highly realistic but fake videos, images even can manipulates the voices. Mar 26, 2024 · This survey comprehensively reviews the latest developments in deepfake generation and detection, summarizing and analyzing current state-of-the-arts in this rapidly evolving field. Deepfake has been a signicant threat to national security, democracy, society, and our privacy, which calls for deepfake detection methods to combat potential threats. Our research confidently addresses the gap in the existing literature on Jun 29, 2022 · The paper [10] discusses how Deepfake videos can be detected and how they are used in digital media forensics. Ethical, legal, and social implications of deepfake technology. Published in: 2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA) All in all, this paper presents an overview of current deepfake and face manipulation techniques by covering four kinds of deepfake or face manipulation. The paper first outlines Mar 2, 2022 · A research paper on the use of deepfake detection to prevent morphing presentation attacks against smart city facial recognition system won the Best Paper Award at the recent OITS/IEEE International Conference on Information Technology, according to an announcement by University of North Texas College of Engineering. To solve this problem, we present DeepFaceLab, the current dominant deepfake framework for face-swapping. In this paper, we consider the deepfake detection technologies Xception and MobileNet as two approaches for classification tasks to automatically detect deepfake Feb 14, 2021 · In the last few years, with the advent of deepfake videos, image forgery has become a serious threat. e. performed a broad analysis in their paper to offer an overview of the research efforts in Deepfake detection, synthesizing 112 published documents from 2018 to 2020 that provided a range of techniques. Our approach uses simple classical frequency analysis at high frequencies to distinguish Apr 9, 2021 · To prevent it from threatening human society, a series of research have been launched, including developing detection methods and building large-scale benchmarks. Furthermore, we report the advantages Sep 21, 2021 · This paper aims to study and analyze the methods to detect Deepfake content and the issues related to the same. Recently, how to detect such forgery contents has become a hot research topic and many deepfake detection methods have been proposed. These datasets have helped enable the development and evaluation of machine learning, and in particular, deep learning models for enhanced deepfake detection. On the one hand, Deepfake has paved the way May 29, 2024 · Deepfake videos are a growing social issue. Guest Convolutional Neural Networks (CNNs). Jul 19, 2022 · researchers choose suitable methods for deepfake research, which paves the way for further improvement. Feb 19, 2020 · In other words, uncertainty about the content of a deepfake mediates the relationship between exposure to a deceitful deepfake and trust in news on social media (H3). Reliability-oriented research challenges of the current Deepfake detection research domain are defined in Much research has been devoted to developing detection methods to reduce the potential negative impact of deepfakes. Recent advances in deepfake generation make deepfake more realistic and easier to make. The approach and its steps are discussed in this paper. Scenarios where these realistic fake videos are used to create political distress, blackmail someone or fake terrorism events are easily envisioned. In this Mar 17, 2021 · Compared with watching scenes of another person, watching your own doppelganger causes encoding of false memories in which participants believe they actually performed the deepfake activity, 7 more exercise behavior after watching a positive health outcome, 8 and brand preference for products used by the virtual self in the deepfake. Dec 1, 2020 · 1. Feb 24, 2022 · To provide an updated overview of the research works in Deepfake detection, we conduct a systematic literature review (SLR) in this paper, summarizing 112 relevant articles from 2018 to 2020 that presented a variety of methodologies. Dec 25, 2023 · This paper presents a detailed review of past and present DeepFake detection methods with a particular focus on media-modality fusion and machine learning. In recent months a machine learning based free software tool has made it easy to create believable face swaps in videos that leaves few traces of manipulation, in what are known as "deepfake" videos. Now, here's an excerpt from a couple years ago: How do you spot a DeepFake? How good are DeepFake videos? Oct 23, 2023 · This survey paper provides a general understanding of deepfakes and their creation; it also presents an overview of state-of-the-art detection techniques, existing datasets curated for deepfake research, as well as associated challenges and future research trends. May 8, 2023 · This paper proposes an automated method to classify deep fake images by employing Deep Learning and Machine Learning based methodologies. Deepfake Detection Challenge invites people to participate in discovering unique solutions for recognizing and avoiding falsified media. For this paper, both relevant and recent research papers need to be selected. In this research, DeepFake detection May 21, 2023 · Deep learning is a sophisticated and adaptable technique that has found widespread use in fields such as natural language processing, machine learning, and computer vision. It also provides a detailed comparison of the objectives, methodology, and algorithms proposed in various studies by different researchers in recent years. The paper discusses prevention and mitigation as countermeasures for deepfake generation. present the recent progress of deepfake detection methods with the open-source deepfake dataset, and iii. In this paper, we highlight a few of these challenges and discuss the research opportunities in this direction. By leveraging a Jul 21, 2018 · Keywords: Deep Fake, Deep Fakes, deepfake, deepfakes, Section 230, CDA University of Maryland Francis King Carey School of Law Legal Studies Research Paper Series Mar 23, 2022 · A number of AI-generated tools are used today to clone human voices, leading to a new technology known as Audio Deepfakes (ADs). Malicious individuals misuse deepfake technologies to spread false information, such as fake images, videos, and audio. The existing standards provide scant guidance because they were developed before the advent of deepfake technology. 51 employed Alex Net for deepfake Nov 1, 2019 · published deepfake research to improve their. ADs have thus recently come to the attention of researchers, with Machine Learning (ML) and Deep Learning (DL) methods being developed to detect them. These commentaries have often been hypothetical, with few real-world cases of deepfake’s political and epistemological harm. While existing methods focus on large and complex models, the need for real-time detection demands greater efficiency. DeepFake Detection is the task of detecting fake videos or images that have been generated using deep learning techniques. Table 1 shows the deepfake datasets with their corresponding statistics, generation methods, and release date. The paper is organized as follows: Method and Materials are conferred in Section 2. Jul 6, 2023 · By shedding light on these critical aspects, this research aims to contribute to a better understanding of the impact of deepfake technology on social media and to inform future efforts in The rest of the article is structured as follows: Section 2 summaries the related work, Section 3 contains deepfake Creation and deep learning Detection Techniques, Section 4 contains the public available dataset used in the Deepfake field, the challenges and the open issues are discussed in Section 5, Section 6 concludes the research. 8). Funding Aug 20, 2018 · The paper’s main contribution is the classification of the many challenges encountered while detecting deepfake videos. The paper thus explores different algorithms used for DeepFake creation and detection; presenting a comprehensive overview of the techniques used and aimed at identifying their pros and cons. This technology poses a significant ethical threat and could lead to breaches of privacy and misrepresentation, thus there is an urgent need for real-time detection of AI-generated speech for DeepFake Voice Conversion. This paper proposes a binary classifier based on a 2-phase learning architecture for detecting DeepFake images and demonstrates 91% validation accuracy on a large, diverse dataset of sophisticated GAN-generated DeepFake images. DeepFakes refer to face multimedia content, which has been digitally altered or synthetically created using deep neural networks. Deepfake technology can be used to perform face manipulation with high realism. By harnessing deep learning methodologies like Recurrent Neural Networks (RNNs), Convolutional Neural Networks (CNNs), and Long Short-Term Memory (LSTM) networks, the paper endeavors to discern tampered videos. As such, future research could further explore the role of emotions in deepfake detection by running experiments with larger the research community. Deepfake is one such emerging technology that allows the creation of highly realistic, believable synthetic content. In this survey, we provide a thorough review of the existing Deepfake detection studies from the reliability perspective. , 2020, Verdoliva, 2020 and Mirsky and Lee (2021). The rise of social media platforms and online forums has exacerbated the challenges of detecting misinformation and malicious content. Oct 14, 2023 · PDF | Deepfake audio refers to synthetically generated audio, often used as legal hoaxes to impersonate human voices. deliver a more precise overview of the different types of deepfake as well as their available generation tools and technology, ii. PF revised the interdisciplinary aspect of the article and provided additional editing. , 2016). Jan 1, 2022 · To provide an updated overview of the research works in Deepfake detection, we conduct a systematic literature review (SLR) in this paper, summarizing 112 relevant articles from 2018 to 2020 To address the survey gap, the paper proposes a comprehensive review of deepfake generation and detection and the different ML/DL approaches to synthesize deepfake contents. We present extensive discussions on challenges, research trends and directions related to deepfake technologies. It is a recent research area in which researchers in academia and industry have contributed deepfake databases, and synthesis and detection algorithms, which has made the deepfake popularity grow. In 2018, it was discovered how easy it is to use this technology for unethical and malicious applications, such as the spread of misinformation, impersonation of political leaders, and the defamation of innocent individuals. These videos are often so sophisticated that traces of manipulation are difficult to detect. Many incredible uses of this technology are being Apr 6, 2021 · This paper presents findings from a systematic review of English-language deepfake research to identify salient discussions. To address May 22, 2024 · Major Internet platforms have also made efforts to contribute to strengthening public deepfake literacy. This paper has reviewed the state-of-the-art methods and a summary of typical approaches is provided in Table 2. Feb 25, 2021 · The existing surveys have mainly focused on the detection of deepfake images and videos. Initially easy to detect, rapid advancements in Mar 25, 2023 · Learn about the history, challenges and applications of deepfake technology, a powerful tool for manipulating digital media, in this comprehensive review. Deepfakes, a term coined in 2017, primarily involve face-swapping in videos. However, this good aspect of Deepfake sometimes pose serious threats to society as malicious intenet users exploit deepfakes to disseminate false information. However, according to the same site, using the same research method, there were 1,333 DeepFake related papers by the end of the year, an increase of about 80% compared to the projection. Check out a video from the Election Misinformation Symposium: Fighting Misinfo Through Fact-checking and Deepfake Detection. As a result, they do not solve the concern of how to deter lawyers from exploiting it. High quality fake videos and audios generated by AI- algorithms (the deep fakes) have started to challenge the status of videos and audios as definitive evidence of events. Most ongoing research aimed at combating the influence of deepfakes has focused on automated deepfake detection: using algorithms to discern if a specific image . DS contributed additional ideas. Additionally, we demonstrate how our system achieves competitive results through a simple and robust approach. In summary, our research aims to address the challenges posed by deepfakes by utilizing AI technologies. we look for DeepFake papers in two popular scientific databases (Google Scholar and DBLP), as well as arXiv, where Feb 1, 2024 · The research underscores methods of DeepFake detection and contemplates the potential influence of DeepFake on democratic procedures and national security. With this in mind, unlike previous work, we introduce a novel deepfake detection approach on images using Binary Neural Networks (BNNs) for fast inference with Mar 3, 2021 · Face forgery by deepfake is widely spread over the internet and has raised severe societal concerns. We discuss a comparative analysis of deepfake models and public datasets present for deepfake detection purposes. Moreover, this work [17] lacks a discussion of audio deepfakes. This Jan 13, 2023 · Advancements in deep learning techniques and the availability of free, large databases have made it possible, even for non-technical people, to either manipulate or generate realistic facial samples for both benign and malicious purposes. Despite being introduced to enhance human lives as audiobooks, ADs have been used to disrupt public safety. In this regard, this study searches the deepfake literature from Web of Science (WoS) and Google Scholar which are prominent scientific research databases. It is one of the most recent deep learning-powered applications to emerge. 036, p = . Oct 31, 2019 · Automated deepfake detection. AI-generated fake images, also known as DeepFakes, are designed to spread abusive content and misinformation amongst millions of people, exacerbated by their Aug 2, 2024 · Big data analytics, computer vision, and human-level governance are key areas where deep learning has been impactful. The paper discusses data challenges such as unbalanced datasets and As there is currently no specific law to address deepfakes, thus deepfake detection, which is an action to discriminate pristine media from deepfake media, plays a vital role in identifying and thwarting deepfake. Deepfake detections are techniques for identifying actual or insightful photographs Jan 9, 2023 · A deepfake is content or material that is synthetically generated or manipulated using artificial intelligence (AI) methods, to be passed off as real and can include audio, video, image, and text Aug 8, 2024 · Deepfake technology has rapidly advanced in recent years, creating highly realistic fake videos that can be difficult to distinguish from real ones. This review aims to demonstrate the current research status of deepfake video detection, especially, generation process, several detection methods and existing benchmarks. These videos are manipulated by artificial intelligence (AI) techniques (especially deep learning), an emerging societal issue. They classified them into four categories: DL-based approaches, traditional ML-based techniques, statistical techniques, and Much research has been devoted to developing detection methods to reduce the potential negative impact of deepfakes. yuezunli/CVPRW2019_Face_Artifacts • • 1 Nov 2018 Compared to previous methods which use a large amount of real and DeepFake generated images to train CNN classifier, our method does not need DeepFake generated images as negative training examples since we target the artifacts in affine face warping as the distinctive feature to Jun 7, 2024 · Deepfake detection aims to contrast the spread of deep-generated media that undermines trust in online content. Jan 17, 2020 · I. So far, there have been a large amount of deepfake videos circulating on the Internet, most of which target at celebrities or politicians. The purpose of this survey is to provide the reader with a deeper understanding of (1) how deepfakes are created and detected, (2) the current trends and advancements in this domain, (3) the shortcomings of the current defense solutions, and (4) the areas that Jan 8, 2022 · Deepfake refers to realistic, but fake images, sounds, and videos generated by articial intelligence methods. Mirsky et al. Jan 1, 2023 · Deepfake is so hard to spot that sometimes not even humans can tell the difference. Find our deepfake research discussed in the news: Science, Scientific American, BBC, WSJ, NYT, , and NPR . JL is the main author of this paper. vwyu dgjqio vilsh hyw ekwi soqlo plc bdlyi aklpvitr ofq