Actor and Action Video Segmentation from a Sentence

This paper strives for pixel-level segmentation of actors and their actions in video content. Different from existing works, which all learn to segment from a fixed vocabulary of actor and action pairs, we infer the segmentation from a natural language input sentence. This allows to distinguish between fine-grained actors in the same super-category, identify actor and action instances, and segment pairs that are outside of the actor and action vocabulary. We propose a fully-convolutional model for pixel-level actor and action segmentation using an encoder-decoder architecture optimized for video. To show the potential of actor and action video segmentation from a sentence, we extend two popular actor and action datasets with more than 7,500 natural language descriptions. Experiments demonstrate the quality of the sentence-guided segmentations, the generalization ability of our model, and its advantage for traditional actor and action segmentation compared to the state-of-the-art.Comment: Accepted to CVPR 2018 as ora

Actor-Transformers for Group Activity Recognition

This paper strives to recognize individual actions and group activities from videos. While existing solutions for this challenging problem explicitly model spatial and temporal relationships based on location of individual actors, we propose an actor-transformer model able to learn and selectively extract information relevant for group activity recognition. We feed the transformer with rich actor-specific static and dynamic representations expressed by features from a 2D pose network and 3D CNN, respectively. We empirically study different ways to combine these representations and show their complementary benefits. Experiments show what is important to transform and how it should be transformed. What is more, actor-transformers achieve state-of-the-art results on two publicly available benchmarks for group activity recognition, outperforming the previous best published results by a considerable margin.Comment: CVPR 202

Cloth in the Wind: A Case Study of Physical Measurement through Simulation

For many of the physical phenomena around us, we have developed sophisticated models explaining their behavior. Nevertheless, measuring physical properties from visual observations is challenging due to the high number of causally underlying physical parameters -- including material properties and external forces. In this paper, we propose to measure latent physical properties for cloth in the wind without ever having seen a real example before. Our solution is an iterative refinement procedure with simulation at its core. The algorithm gradually updates the physical model parameters by running a simulation of the observed phenomenon and comparing the current simulation to a real-world observation. The correspondence is measured using an embedding function that maps physically similar examples to nearby points. We consider a case study of cloth in the wind, with curling flags as our leading example -- a seemingly simple phenomena but physically highly involved. Based on the physics of cloth and its visual manifestation, we propose an instantiation of the embedding function. For this mapping, modeled as a deep network, we introduce a spectral layer that decomposes a video volume into its temporal spectral power and corresponding frequencies. Our experiments demonstrate that the proposed method compares favorably to prior work on the task of measuring cloth material properties and external wind force from a real-world video.Comment: CVPR 2020. arXiv admin note: substantial text overlap with arXiv:1910.0786

Digital process simulation twins using statistics and information technologies

This article presents the prospects for the development of virtual mathematical modeling of technological processes of various technical levels to simplify the process of manufacturing functional parts in production areas. A calculation model was drawn up, on the basis of which the thermal task was set for calculation, a change in temperature over a certain period of time was demonstrated. A study was also carried out aimed at identifying energy losses in the technological process, the main technical parameters of which are also presented in the materials of this work. The presented data confirm the practical significance of this and are aimed at stabilization of both technical and technological processes. The study conducted in the article is provided with graphic materials when entering and outputting information, tables with results, as well as a detailed description of each stage of the study

The “Angiogenic Switch” and Functional Resources in Cyclic Sports Athletes

Regular physical activity in cyclic sports can influence the so-called “angiogenic switch”, which is considered as an imbalance between proangiogenic and anti-angiogenic molecules. Disruption of the synthesis of angiogenic molecules can be caused by local changes in tissues under the influence of excessive physical exertion and its consequences, such as chronic oxidative stress and associated hypoxia, metabolic acidosis, sports injuries, etc. A review of publications on signaling pathways that activate and inhibit angiogenesis in skeletal muscles, myocardium, lung, and nervous tissue under the influence of intense physical activity in cyclic sports. Materials: We searched PubMed, SCOPUS, Web of Science, Google Scholar, Clinical keys, and e-LIBRARY databases for full-text articles published from 2000 to 2020, using keywords and their combinations. Results: An important aspect of adaptation to training loads in cyclic sports is an increase in the number of capillaries in muscle fibers, which improves the metabolism of skeletal muscles and myocardium, as well as nervous and lung tissue. Recent studies have shown that myocardial endothelial cells not only respond to hemodynamic forces and paracrine signals from neighboring cells, but also take an active part in heart remodeling processes, stimulating the growth and contractility of cardiomyocytes or the production of extracellular matrix proteins in myofibroblasts. As myocardial vascularization plays a central role in the transition from adaptive heart hypertrophy to heart failure, further study of the signaling mechanisms involved in the regulation of angiogenesis in the myocardium is important in sports practice. The study of the “angiogenic switch” problem in the cerebrovascular and cardiovascular systems allows us to claim that the formation of new vessels is mediated by a complex interaction of all growth factors. Although the lungs are one of the limiting systems of the body in cyclic sports, their response to high-intensity loads and other environmental stresses is often overlooked. Airway epithelial cells are the predominant source of several growth factors throughout lung organogenesis and appear to be critical for normal alveolarization, rapid alveolar proliferation, and normal vascular development. There are many controversial questions about the role of growth factors in the physiology and pathology of the lungs. The presented review has demonstrated that when doing sports, it is necessary to give a careful consideration to the possible positive and negative effects of growth factors on muscles, myocardium, lung tissue, and brain. Primarily, the “angiogenic switch” is important in aerobic sports (long distance running). Conclusions: Angiogenesis is a physiological process of the formation of new blood capillaries, which play an important role in the functioning of skeletal muscles, myocardium, lung, and nervous tissue in athletes. Violation of the “angiogenic switch” as a balance between proangiogenic and anti-angiogenic molecules can lead to a decrease in the functional resources of the nervous, musculoskeletal, cardiovascular, and respiratory systems in athletes and, as a consequence, to a decrease in sports performance

A review of GPS/GLONASS studies of the ionospheric response to natural and anthropogenic processes and phenomena

The article is a review of studies of ionospheric effects carried out in ISTP SB RAS. The main results of GPS/GLONASS radio sounding of ionospheric disturbances of natural and anthropogenic origin are presented. The article is devoted to ionospheric effects of solar eclipses, solar flares, solar terminator, earthquakes, tropical cyclones, large-scale ionospheric disturbances of auroral origin, rocket launches. Dynamics of global electron content analysis is also presented. The special attention is paid on the influence of solar flares and ionospheric irregularities on GPS and GLONASS performance. The work is a tribute to the leader of GNSS-monitoring workgroup Prof. E.L. Afraimovich (12 March 1940–8 November 2009)

A review of GPS/GLONASS studies of the ionospheric response to natural and anthropogenic processes and phenomena

The article is a review of studies of ionospheric effects carried out in ISTP SB RAS. The main results of GPS/GLONASS radio sounding of ionospheric disturbances of natural and anthropogenic origin are presented. The article is devoted to ionospheric effects of solar eclipses, solar flares, solar terminator, earthquakes, tropical cyclones, large-scale ionospheric disturbances of auroral origin, rocket launches. Dynamics of global electron content analysis is also presented. The special attention is paid on the influence of solar flares and ionospheric irregularities on GPS and GLONASS performance. The work is a tribute to the leader of GNSS-monitoring workgroup Prof. E.L. Afraimovich (12 March 1940–8 November 2009)

Observation of WWW Production in pp Collisions at √s = 13 TeV with the ATLAS Detector

This Letter reports the observation of W W W production and a measurement of its cross section using 139     fb − 1 of proton-proton collision data recorded at a center-of-mass energy of 13 TeV by the ATLAS detector at the Large Hadron Collider. Events with two same-sign leptons (electrons or muons) and at least two jets, as well as events with three charged leptons, are selected. A multivariate technique is then used to discriminate between signal and background events. Events from W W W production are observed with a significance of 8.0 standard deviations, where the expectation is 5.4 standard deviations. The inclusive W W W production cross section is measured to be 820 ± 100   ( stat ) ± 80   ( syst )     fb , approximately 2.6 standard deviations from the predicted cross section of 511 ± 18     fb calculated at next-to-leading-order QCD and leading-order electroweak accuracy