Bidirectional path tracing (BDPT) with Multiple Importance Sampling is one of the most versatile unbiased rendering algorithms today. BDPT repeatedly generates sub‐paths from the eye and the lights, ...which are connected for each pixel and then discarded. Unfortunately, many such bidirectional connections turn out to have low contribution to the solution. Our key observation is that we can importance sample connections to an eye sub‐path by considering multiple light sub‐paths at once and creating connections probabilistically. We do this by storing light paths, and estimating probability mass functions of the discrete set of possible connections to all light paths. This has two key advantages: we efficiently create connections with low variance by Monte Carlo sampling, and we reuse light paths across different eye paths. We also introduce a caching scheme by deriving an approximation to sub‐path contribution which avoids high‐dimensional path distance computations. Our approach builds on caching methods developed in the different context of VPLs. Our Probabilistic Connections for Bidirectional Path Tracing approach raises a major challenge, since reuse results in high variance due to correlation between paths. We analyze the problem of path correlation and derive a conservative upper bound of the variance, with computationally tractable sample weights. We present results of our method which shows significant improvement over previous unbiased global illumination methods, and evaluate our algorithmic choices.
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Mood disorders and Major Depressive Disorder, in particular, appear to be some of the most common psychiatric disorders with a high rate of comorbidity most frequently of anxiety or substance abuse ...disorders (alcohol use disorder). In both cases - MDD and AUD, a number of immunological disturbances are observed, such as chronic mild inflammation response, increased level of cytokines, hypercortisolaemia, which lead to specific changes in brain neurotransmitter functions. Some of the contemporary brain imaging techniques are functional magnetic resonance imaging (fMRI) and magnetic spectroscopy which are most commonly used to assess the brain metabolism and functional connectivity changes such as altered responses to emotional stimuli in MDD or overactivation of ventromedial prefrontal areas during delayed and underactivation of dorsolateral prefrontal regions during impulsive reward decisions in AUD and dysfunction of gamma-aminobutyric acid (GABA) and/or glutamate neurotransmitter systems, low NAA and myo-Inositol in both MDD and AUD.
The article states an approach for developing a distributed application architecture for dynamic systems analysis in a hybrid cloud. The problem that was posed as an example is based on the ...calculation of the Lyapunov characteristic exponents for trajectories of dynamical systems in phase space. Parallelization of the computational process is achieved by supplying the list of running tasks for computing Lyapunov characteristic exponents, depending on the result of finished tasks during calculations. We have implemented a distributed application to make this experiment automated. The architecture of application elements is established on the principles of the enterprise desktop grid and cloud systems. A vital detail of the application architecture is the deployment process based on a cloud hybrid computing environment using the Jupyter server running on the DigitalOcean cloud platform and the Everest cloud platform simultaneously with the Maple package.
Attachment theory is widely regarded as one of the most significant advancements in psychology. Originally focused on early childhood development, it has expanded to offer insights into a broad ...spectrum of psychological disorders in adulthood. Additionally, some scholars propose that attachment theory could serve as a unifying framework in psychotherapy. If psychological disorders stem from attachment disturbances, then therapeutic interventions should theoretically impact attachment styles. However, there remains ongoing debate regarding whether attachment styles remain fixed throughout life or can adapt in response to environmental factors or psychotherapy. This theoretical study seeks to provide greater clarity on the malleability of attachment styles, the association between attachment and psychological disorders, and the examination of mentalizationa central concept in the genesis of psychological disorders. Mentalization is not only seen as a core feature of attachment styles but also as a key process in psychotherapy.
Vector graphics represent images with compact, editable and scalable primitives. Skillful vector artists employ these primitives to produce vivid depictions of material appearance and lighting. ...However, such stylized imagery often requires building complex multi-layered combinations of colored fills and gradient meshes. We facilitate this task by introducing vector shade trees that bring to vector graphics the flexibility of modular shading representations as known in the 3D rendering community. In contrast to traditional shade trees that combine pixel and vertex shaders, our shade nodes encapsulate the creation and blending of vector primitives that vector artists routinely use. We propose a set of basic shade nodes that we design to respect the traditional guidelines on material depiction described in drawing books and tutorials. We integrate our representation as an Adobe Illustrator plug-in that allows even inexperienced users to take a line drawing, apply a few clicks and obtain a fully colored illustration. More experienced artists can easily refine the illustration, adding more details and visual features, while using all the vector drawing tools they are already familiar with. We demonstrate the power of our representation by quickly generating illustrations of complex objects and materials.
Attachment theory provides a powerful framework for understanding individual differences that affect interpersonal relationships, as well as a range of outcomes related to risky behaviors in various ...life domains. Existing research on the relationship between attachment styles and risk-taking is contradictory and confusing. On the one hand, there is research and the common belief that individuals with secure attachments view the world as a safe place, hence we expect these individuals to be more able to explore the world and take risks, and on the other hand, there is a body of research that highlights that individuals with insecure attachments are more likely to take on risky behaviours. The present article aims to bring more conceptual clarity in understanding and interpreting the conflicting findings about individuals’ ability to take risks based on attachment style.
Realistic rendering requires computing the global illumination in the scene, and Monte Carlo integration is the best‐known method for doing that. The key to good performance is to carefully select ...the costly integration samples, which is usually achieved via importance sampling. Unfortunately, visibility is difficult to factor into the importance distribution, which can greatly increase variance in highly occluded scenes with complex illumination. In this paper, we present importance caching – a novel approach that selects those samples with a distribution that includes visibility, while maintaining efficiency by exploiting illumination smoothness. At a sparse set of locations in the scene, we construct and cache several types of probability distributions with respect to a set of virtual point lights (VPLs), which notably include visibility. Each distribution type is optimized for a specific lighting condition. For every shading point, we then borrow the distributions from nearby cached locations and use them for VPL sampling, avoiding additional bias. A novel multiple importance sampling framework finally combines the many estimators. In highly occluded scenes, where visibility is a major source of variance in the incident radiance, our approach can reduce variance by more than an order of magnitude. Even in such complex scenes we can obtain accurate and low noise previews with full global illumination in a couple of seconds on a single mid‐range CPU.
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Manually annotating object segmentation masks is very time consuming. Interactive object segmentation methods offer a more efficient alternative where a human annotator and a machine segmentation ...model collaborate. In this paper we make several contributions to interactive segmentation: (1) we systematically explore in simulation the design space of deep interactive segmentation models and report new insights and caveats; (2) we execute a large-scale annotation campaign with real human annotators, producing masks for 2.5M instances on the OpenImages dataset. We released this data publicly, forming the largest existing dataset for instance segmentation. Moreover, by re-annotating part of the COCO dataset, we show that we can produce instance masks 3x faster than traditional polygon drawing tools while also providing better quality. (3) We present a technique for automatically estimating the quality of the produced masks which exploits indirect signals from the annotation process.
The Open Images Dataset V4 Kuznetsova, Alina; Rom, Hassan; Alldrin, Neil ...
International journal of computer vision,
07/2020, Volume:
128, Issue:
7
Journal Article
Peer reviewed
Open access
We present Open Images V4, a dataset of 9.2M images with unified annotations for image classification, object detection and visual relationship detection. The images have a Creative Commons ...Attribution license that allows to share and adapt the material, and they have been collected from Flickr without a predefined list of class names or tags, leading to natural class statistics and avoiding an initial design bias. Open Images V4 offers large scale across several dimensions: 30.1M image-level labels for 19.8k concepts, 15.4M bounding boxes for 600 object classes, and 375k visual relationship annotations involving 57 classes. For object detection in particular, we provide
15
×
more bounding boxes than the next largest datasets (15.4M boxes on 1.9M images). The images often show complex scenes with several objects (8 annotated objects per image on average). We annotated visual relationships between them, which support visual relationship detection, an emerging task that requires structured reasoning. We provide in-depth comprehensive statistics about the dataset, we validate the quality of the annotations, we study how the performance of several modern models evolves with increasing amounts of training data, and we demonstrate two applications made possible by having unified annotations of multiple types coexisting in the same images. We hope that the scale, quality, and variety of Open Images V4 will foster further research and innovation even beyond the areas of image classification, object detection, and visual relationship detection.
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