Target Actor Research Articles

Towards a better identification of Bitcoin actors by supervised learning

Bitcoin is the most widely used crypto-currency, and one of the most studied. Thanks to the open nature of the Blockchain, transaction records are freely accessible and can be analyzed by anyone. The first step in most analytics work is to group anonymous addresses into a set of addresses, called aggregates, that are meant to correspond to unique actors. In this paper, we propose new methods to discover more accurate address aggregates using supervised learning. We introduce a way to create a labeled training set based on reliable heuristics and external information, and propose two methods. The first method automatically finds address aggregates from a set of transactions. The second one improves an address aggregate of a target actor by specializing the training for a single actor. We empirically validate our results on large-scale datasets. A striking result of our analysis is that training a model to recognize the change addresses of a particular actor is more efficient than using a larger dataset that does not target that particular actor. In doing so, we clearly show the feasibility and interest of supervised machine learning to identify Bitcoin actors.

Learning Dynamic 3D Geometry and Texture for Video Face Swapping

AbstractFace swapping is the process of applying a source actor's appearance to a target actor's performance in a video. This is a challenging visual effect that has seen increasing demand in film and television production. Recent work has shown that data‐driven methods based on deep learning can produce compelling effects at production quality in a fraction of the time required for a traditional 3D pipeline. However, the dominant approach operates only on 2D imagery without reference to the underlying facial geometry or texture, resulting in poor generalization under novel viewpoints and little artistic control. Methods that do incorporate geometry rely on pre‐learned facial priors that do not adapt well to particular geometric features of the source and target faces. We approach the problem of face swapping from the perspective of learning simultaneous convolutional facial autoencoders for the source and target identities, using a shared encoder network with identity‐specific decoders. The key novelty in our approach is that each decoder first lifts the latent code into a 3D representation, comprising a dynamic face texture and a deformable 3D face shape, before projecting this 3D face back onto the input image using a differentiable renderer. The coupled autoencoders are trained only on videos of the source and target identities, without requiring 3D supervision. By leveraging the learned 3D geometry and texture, our method achieves face swapping with higher quality than when using off‐the‐shelf monocular 3D face reconstruction, and overall lower FID score than state‐of‐the‐art 2D methods. Furthermore, our 3D representation allows for efficient artistic control over the result, which can be hard to achieve with existing 2D approaches.

Iterative Text-Based Editing of Talking-Heads Using Neural Retargeting

We present a text-based tool for editing talking-head video that enables an iterative editing workflow. On each iteration users can edit the wording of the speech, further refine mouth motions if necessary to reduce artifacts, and manipulate non-verbal aspects of the performance by inserting mouth gestures (e.g., a smile) or changing the overall performance style (e.g., energetic, mumble). Our tool requires only 2 to 3 minutes of the target actor video and it synthesizes the video for each iteration in about 40 seconds, allowing users to quickly explore many editing possibilities as they iterate. Our approach is based on two key ideas. (1) We develop a fast phoneme search algorithm that can quickly identify phoneme-level subsequences of the source repository video that best match a desired edit. This enables our fast iteration loop. (2) We leverage a large repository of video of a source actor and develop a new self-supervised neural retargeting technique for transferring the mouth motions of the source actor to the target actor. This allows us to work with relatively short target actor videos, making our approach applicable in many real-world editing scenarios. Finally, our, refinement and performance controls give users the ability to further fine-tune the synthesized results.

Eighty-six EU policy options for reducing imported deforestation

Eighty-six EU policy options for reducing imported deforestation

Strategi Jaringan Advokasi Transnasional Greenpeace Indonesia Terkait Isu Deforestasi Hutan Indonesia oleh Wilmar International

Greenpeace Indonesia saat ini menyoroti Wilmar Internasional sebagai pelaku deforestasi. Greenpeace Indonesia menekan Wilmar International untuk berkomitmen mengimplementasikan kebijakan No Deforestation, No Peat, No Exploitation (NDPE) mereka lewat pembentukan jaringan advokasi transnasional guna membuat powernya cukup untuk menekan Wilmar International. Lewat metode tersebut, Greenpeace Indonesia berhasil membuat Wilmar International terdesak dan merubah perilakunya. Penelitian ini menganalisis bagaimana strategi Greenpeace Indonesia dalam membentuk jaringan advokasi transnasional hingga jaringan tersebut menekan dan memantau perilaku aktor target melalui teori Transnational Advocacy Network Keck & Sikkink. Peneliti menggunakan metode kualitatif dengan pendekatan studi kasus. Pengumpulan data berasal dari data primer dan sekunder serta pengumpulan data melalui studi kepustakaan dari buku, jurnal dan artikel. Hasil penelitian ini menunjukkan bahwa Greenpeace Indonesia sangat optimal dalam melakukan strategi Information Politics dan Leverage Politics. Greenpeace Indonesia memiliki metode yang kreatif dan konfrontatif dalam mengimplementasikan strategi Symbolic Politics. Tetapi kelemahan dari strategi ini yaitu Greenpeace Indonesia terkesan eksklusif dalam melakukan aksi-aksinya oleh NGO lingkungan lain khususnya NGO lingkungan yang basisnya domestik. Kelemahan dari empat strategi ini yaitu Accountability Politics dimana Greenpeace Indonesia tidak memiliki komitmen dari Wilmar International yang memiliki kekuatan hukum mengikat sehingga Greenpeace Indonesia hanya mengandalkan tekanan publik dalam menekan Wilmar International guna berkomitmen menjalankan kebijakan NDPE.

Entrapping Gulliver: The United States and the Antipersonnel Mine Ban

In 2014, the Obama administration announced that the United States would almost entirely adopt the global ban on antipersonnel (AP) mines, despite longstanding military and political opposition. To explain this puzzling outcome, I expand upon recent accounts of rhetorical entrapment in which norm-promoting actors seek to compel change in a target actor by exploiting tensions between the target’s words and actions. Tracing US policy change over the past 25 years, I show how transnational civil society and domestic political elites strategically deployed factual and normative claims to draw US officials into an iterative debate concerning the humanitarian harm of AP mines. Successive US administrations have sought to mitigate external critique by gradually conceding to the discursive framing of pro-ban advocates without endorsing the international treaty prohibiting the weapons. These rhetorical shifts stimulated a search for alternative technologies and incremental changes to military doctrine, tactics, and procurement that constrained US policy choices, culminating in the effective abandonment of AP mines despite ongoing military operations around the globe.

Neural style-preserving visual dubbing

Dubbing is a technique for translating video content from one language to another. However, state-of-the-art visual dubbing techniques directly copy facial expressions from source to target actors without considering identity-specific idiosyncrasies such as a unique type of smile. We present a style-preserving visual dubbing approach from single video inputs, which maintains the signature style of target actors when modifying facial expressions, including mouth motions, to match foreign languages. At the heart of our approach is the concept of motion style, in particular for facial expressions, i.e., the person-specific expression change that is yet another essential factor beyond visual accuracy in face editing applications. Our method is based on a recurrent generative adversarial network that captures the spatiotemporal co-activation of facial expressions, and enables generating and modifying the facial expressions of the target actor while preserving their style. We train our model with unsynchronized source and target videos in an unsupervised manner using cycle-consistency and mouth expression losses, and synthesize photorealistic video frames using a layered neural face renderer. Our approach generates temporally coherent results, and handles dynamic backgrounds. Our results show that our dubbing approach maintains the idiosyncratic style of the target actor better than previous approaches, even for widely differing source and target actors.

Deep Video‐Based Performance Cloning

AbstractWe present a new video‐based performance cloning technique. After training a deep generative network using a reference video capturing the appearance and dynamics of a target actor, we are able to generate videos where this actor reenacts other performances. All of the training data and the driving performances are provided as ordinary video segments, without motion capture or depth information. Our generative model is realized as a deep neural network with two branches, both of which train the same space‐time conditional generator, using shared weights. One branch, responsible for learning to generate the appearance of the target actor in various poses, uses paired training data, self‐generated from the reference video. The second branch uses unpaired data to improve generation of temporally coherent video renditions of unseen pose sequences. Through data augmentation, our network is able to synthesize images of the target actor in poses never captured by the reference video. We demonstrate a variety of promising results, where our method is able to generate temporally coherent videos, for challenging scenarios where the reference and driving videos consist of very different dance performances.

Headon

We propose HeadOn, the first real-time source-to-target reenactment approach for complete human portrait videos that enables transfer of torso and head motion, face expression, and eye gaze. Given a short RGB-D video of the target actor, we automatically construct a personalized geometry proxy that embeds a parametric head, eye, and kinematic torso model. A novel realtime reenactment algorithm employs this proxy to photo-realistically map the captured motion from the source actor to the target actor. On top of the coarse geometric proxy, we propose a video-based rendering technique that composites the modified target portrait video via view- and pose-dependent texturing, and creates photo-realistic imagery of the target actor under novel torso and head poses, facial expressions, and gaze directions. To this end, we propose a robust tracking of the face and torso of the source actor. We extensively evaluate our approach and show significant improvements in enabling much greater flexibility in creating realistic reenacted output videos.

Deep video portraits

We present a novel approach that enables photo-realistic re-animation of portrait videos using only an input video. In contrast to existing approaches that are restricted to manipulations of facial expressions only, we are the first to transfer the full 3D head position, head rotation, face expression, eye gaze, and eye blinking from a source actor to a portrait video of a target actor. The core of our approach is a generative neural network with a novel space-time architecture. The network takes as input synthetic renderings of a parametric face model, based on which it predicts photo-realistic video frames for a given target actor. The realism in this rendering-to-video transfer is achieved by careful adversarial training, and as a result, we can create modified target videos that mimic the behavior of the synthetically-created input. In order to enable source-to-target video re-animation, we render a synthetic target video with the reconstructed head animation parameters from a source video, and feed it into the trained network - thus taking full control of the target. With the ability to freely recombine source and target parameters, we are able to demonstrate a large variety of video rewrite applications without explicitly modeling hair, body or background. For instance, we can reenact the full head using interactive user-controlled editing, and realize high-fidelity visual dubbing. To demonstrate the high quality of our output, we conduct an extensive series of experiments and evaluations, where for instance a user study shows that our video edits are hard to detect.

Encoding of event roles from visual scenes is rapid, spontaneous, and interacts with higher-level visual processing

A crucial component of event recognition is understanding event roles, i.e. who acted on whom: boy hitting girl is different from girl hitting boy. We often categorize Agents (i.e. the actor) and Patients (i.e. the one acted upon) from visual input, but do we rapidly and spontaneously encode such roles even when our attention is otherwise occupied? In three experiments, participants observed a continuous sequence of two-person scenes and had to search for a target actor in each (the male/female or red/blue-shirted actor) by indicating with a button press whether the target appeared on the left or the right. Critically, although role was orthogonal to gender and shirt color, and was never explicitly mentioned, participants responded more slowly when the target’s role switched from trial to trial (e.g., the male went from being the Patient to the Agent). In a final experiment, we demonstrated that this effect cannot be fully explained by differences in posture associated with Agents and Patients. Our results suggest that extraction of event structure from visual scenes is rapid and spontaneous.

Foreign Policy Attitudes toward Islamic Actors

This article examines how Western foreign policy opinion reacts to the perceived Islamic character of foreign actors. Studies show that the target actor’s dominant religion is a key ingredient in foreign policy opinion: Western audiences react more hostilely to “Muslim” than “Christian” targets. Yet, actors differ not only in which world religion they belong to but also how that religion is politicized by themselves and by others. We argue that Islam can be politicized in three major ways—via Islamic rhetoric, policies, and labels—that shape foreign policy attitudes. To examine our claims, we field a survey experiment in which we attach common Islamic rhetoric (“Allahu Akbar”), policies (“Shari’a law”), and/or labels (“Islamist”) to a foreign actor in the context of the Syrian civil conflict. We find that these cues strongly harm attitudes toward the actor, and the results vary widely by type. Indeed, the Shari’a policy cue does the most damage to attitudes, emotions, and preferences toward the actor. Moreover, the Islamic cues reinforce each other in fueling these fearful reactions and are particularly potent on conservative citizens. These results paint a richer picture of how out-group religious cues influence foreign policy attitudes.

Real-time expression transfer for facial reenactment

We present a method for the real-time transfer of facial expressions from an actor in a source video to an actor in a target video, thus enabling the ad-hoc control of the facial expressions of the target actor. The novelty of our approach lies in the transfer and photorealistic re-rendering of facial deformations and detail into the target video in a way that the newly-synthesized expressions are virtually indistinguishable from a real video. To achieve this, we accurately capture the facial performances of the source and target subjects in real-time using a commodity RGB-D sensor. For each frame, we jointly fit a parametric model for identity, expression, and skin reflectance to the input color and depth data, and also reconstruct the scene lighting. For expression transfer, we compute the difference between the source and target expressions in parameter space, and modify the target parameters to match the source expressions. A major challenge is the convincing re-rendering of the synthesized target face into the corresponding video stream. This requires a careful consideration of the lighting and shading design, which both must correspond to the real-world environment. We demonstrate our method in a live setup, where we modify a video conference feed such that the facial expressions of a different person (e.g., translator) are matched in real-time.

PATERNALISM AND GLOBAL GOVERNANCE

Abstract:Contemporary global governance is organized around an odd pairing: care and control. On the one hand, much of global governance is designed to reduce human suffering and improve human flourishing, with the important caveat that individuals should be allowed to decide for themselves how they want to live their lives. On the other hand, these global practices of care are also entangled with acts of control. Peacebuilding, public health, emergency aid, human rights, and development are expressions of this tension between care and control. There is a concept that captures this tension: paternalism. Drawing on our moral intuitions, I argue that paternalism is the attempt by one actor to substitute his judgment for another actor's on the grounds that such an imposition will improve the welfare of the target actor. After discussing and defending this definition, I note how our unease with paternalism seems to grow as we scale up from the interpersonal to the international, which I argue owes to the evaporation of community and equality. After exploring the implications of this definition and distinguishing it from other forms of intervention, I consider how different elements of paternalism combine to generate different configurations. Specifically, I point to five dimensions that are most relevant for examining the paternalism found in contemporary global and humanitarian governance: the tools used to restrict another actor’s liberty (force versus information); the scope of the interference (wide versus narrow); the purpose of the intervention (prevention of harm versus emancipation); the source of the paternalizer’s confidence (faith versus evidence); and the mechanisms of accountability (internal versus external). These different elements often correlate historically, suggestive of two ideal types of global paternalism: strong and weak. Contemporary global and humanitarian governance is largely the weak variety: force is severely proscribed, interference is relatively restricted, the paternalizer’s confidence has epistemic roots, and accountability to local populations remains a noble but rarely practiced goal. I further speculate that a major reason for this difference is the effects of liberalism and rationalization. I use this taxonomy to suggest how two different global efforts to improve the lives of those peoples living in what were perceived to be unstable and illiberal territories — the civilizing missions of the nineteenth century and the peacebuilding operations of the post-Cold War period — exhibited different kinds of paternalism. I conclude by reflecting on the ethics of international paternalism.

A CROSS-CULTURAL COMPARISON BETWEEN AMERICANS AND CHINESE IN THEIR ATTITUDES TOWARDS INFORMATION ETHICS

The purpose of this study is twofold: first to explore cross-cultural differences between American and Chinese business students with respect to their attitudes towards information ethics; and second to investigate the association between their ethical evaluations of the target act and their morality judgments of the target actor in the questionable information-handling issues. Using a sample of 105 American business students and 98 Chinese business students, this study found that the Chinese students tended to be more ethical in the questionable privacy and access issues, whereas their American counterparts were more likely to be ethical in the questionable property issue. In addition, the female students, regardless of their culture backgrounds, were more ethical than the male students. The results further revealed that the students' ethical evaluations of the target act were significantly related to their morality judgments of the target actor. Implications for practitioners, educators, and researchers are discussed.

Network centrality and social movement media coverage: A two-mode network analytic approach

This article examines the relationship between structural location (namely, degree centrality) and news media coverage. Our central hypothesis is that the network centrality of social movement actors is positively associated with the prevalence of actors being cited in the print news media. This paper uses two-mode data from a communication network of environmentalists in British Columbia, and examines the relationship between their structural location and the frequency by which they are cited in newsprint media with regard to particular frames (about forest conservation, environmental protest, and related issues). We asked a sample of social movement participants about their ties to a target list of relatively high profile actors (environmental activists). We turned the resulting network matrix into a bipartite graph that examined the relationships amongst the target actors vis a vis the respondents. Next we calculated point in-degree for the target actors. For the target actors we also have data from a representative sample of 957 print news articles about forestry and conservation of old growth forests in British Columbia. We compare the effects of network centrality of the target actor versus several attributes of the target actors (gender, level of radicalism, leadership status) on the amount of media coverage that each of the target actors receives. We find that network centrality is associated with media coverage controlling for actor attributes. We discuss theoretical implications of this research. Finally, we also discuss the methodological pros and cons of using a “target name roster” to construct two-mode data on social movement activists.

Approximating character biomechanics with real‐time weighted inverse kinematics

AbstractIn this paper we show how the expensive, offline dynamic simulations of character motions can be approximated using the cheaper weighted inverse kinematics (WIK)‐based approach. We first show how a dynamics‐based approach can be used to produce a motion that is representative of a real target actor using the motion of a different source actor and the biomechanics of the target actor. This is compared against a process that uses WIK to achieve the same motion mapping goal without direct biomechanical input. The parallels between the results of the two approaches are described and further reasoned from a mathematical perspective. Thus we demonstrate how character biomechanics can be approximated with real‐time WIK. Copyright © 2007 John Wiley & Sons, Ltd.

The situated person: Effects of construct accessibility on situation construals and interpersonal perception

Three studies examined the interrelationship between primed constructs, situation construal, and person perception. Previous research on priming and person perception has generally neglected the situational context. We predicted that when rich situational information is included, primed constructs can lead to assimilation effects on situation construals, which can in turn lead to contrast effects in person perceptions. Study 1 demonstrated that when situation information is included in the experimental context, primes lead to contrast in person perceptions. Study 2, employing a subliminal methodology, demonstrated that these effects could not be accounted for via previous explanations of contrast effects, such as correction-based mechanisms, that require overt recognition of the priming stimuli by the participants. Study 3 demonstrated that the contrastive effects of the priming stimuli on person perception obtained in Studies 1 and 2 are in fact due to the intervening assimilative effects of the priming stimuli on situation construal—that is, the primed constructs led to contrast effects on perceptions of the actor via their assimilative effects on perceptions of the situation in which that actor was embedded. Additionally, moderator variables demonstrated that this effect is most pronounced when the target actor’s behavior is described as relatively unambiguous or situation focus is increased.

Effect of counterfactual and factual thinking on causal judgements

The significance of counterfactual thinking in the causal judgement process has been emphasized for nearly two decades, yet no previous research has directly compared the relative effect of thinking counterfactually versus factually on causal judgement. Three experiments examined this comparison by manipulating the task frame used to focus participants' thinking about a target event. Prior to making judgements about causality, preventability, blame, and control, participants were directed to think about a target actor either in counterfactual terms (what the actor could have done to change the outcome) or in factual terms (what the actor had done that led to the outcome). In each experiment, the effect of counterfactual thinking did not differ reliably from the effect of factual thinking on causal judgement. Implications for research on causal judgement and mental representation are discussed.

How We Explain Depends on Whom We Explain: The Impact of Social Category on the Selection of Causal Comparisons and Causal Explanations

Prior research indicates that people's causal explanations depend on the comparison case against which the event is considered. The present research examined the hypothesis that the causal comparison depends on the typicality of the target actor's social category. Participants in two studies placed greater relative emphasis on across-group comparisons than within-group comparisons for atypical actors compared to typical actors. Perceived typicallity was manipulated indirectly through prior beliefs about the type of person most likely to be involved in an activity (Experiment 1) and directly through explicit information about social group typicality relative to an event (Experiment 2). Participants' causal explanations also differed by social category, providing more category-related explanations for atypical actors than typical actors. The contribution of findings toward understanding the influence of a target actor's group membership on causal explanations is discussed. Findings are also related to prior research on social identity and stereotypes, which has addressed the impact of social category on causal explanations.