Tex2Shape: Detailed Full Human Body Geometry From a Single Image

We present a simple yet effective method to infer detailed full human body shape from only a single photograph. Our model can infer full-body shape including face, hair, and clothing including wrinkles at interactive frame-rates. Results feature details even on parts that are occluded in the input image. Our main idea is to turn shape regression into an aligned image-to-image translation problem. The input to our method is a partial texture map of the visible region obtained from off-the-shelf methods. From a partial texture, we estimate detailed normal and vector displacement maps, which can be applied to a low-resolution smooth body model to add detail and clothing. Despite being trained purely with synthetic data, our model generalizes well to real-world photographs. Numerous results demonstrate the versatility and robustness of our method

Spatial repartition of local plastic processes in different creep regimes in a granular material

Granular packings under constant shear stress display below the Coulomb limit, a logarithmic creep dynamics. However the addition of small stress modulations induces a linear creep regime characterized by an effective viscous response. Using Diffusing Wave Spectroscopy, we investigate the relation between creep and local plastic events spatial distribution ("hot-spots") contributing to the plastic yield. The study is done in the two regimes, i.e. with and without mechanical activation. The hot-spot dynamics is related to the material effective fluidity. We show that far from the threshold, a local visco-elastic rheology coupled to an ageing of the fluidity parameter, is able to render the essential spatio-temporal features of the observed creep dynamics

Learning to Reconstruct People in Clothing from a Single RGB Camera

We present a learning-based model to infer the personalized 3D shape of people from a few frames (1-8) of a monocular video in which the person is moving, in less than 10 seconds with a reconstruction accuracy of 5mm. Our model learns to predict the parameters of a statistical body model and instance displacements that add clothing and hair to the shape. The model achieves fast and accurate predictions based on two key design choices. First, by predicting shape in a canonical T-pose space, the network learns to encode the images of the person into pose-invariant latent codes, where the information is fused. Second, based on the observation that feed-forward predictions are fast but do not always align with the input images, we predict using both, bottom-up and top-down streams (one per view) allowing information to flow in both directions. Learning relies only on synthetic 3D data. Once learned, the model can take a variable number of frames as input, and is able to reconstruct shapes even from a single image with an accuracy of 6mm. Results on 3 different datasets demonstrate the efficacy and accuracy of our approach

Carbon burning in intermediate mass primordial stars

The evolution of a zero metallicity 9 M_s star is computed, analyzed and compared with that of a solar metallicity star of identical ZAMS mass. Our computations range from the main sequence until the formation of a massive oxygen-neon white dwarf. Special attention has been payed to carbon burning in conditions of partial degeneracy as well as to the subsequent thermally pulsing Super-AGB phase. The latter develops in a fashion very similar to that of a solar metallicity 9 M_s star, as a consequence of the significant enrichment in metals of the stellar envelope that ensues due to the so-called third dredge-up episode. The abundances in mass of the main isotopes in the final ONe core resulting from the evolution are X(^{16}O) approx 0.59, X(^{20}Ne) approx 0.28 and X(^{24}Mg) approx 0.05. This core is surrounded by a 0.05 M_s buffer mainly composed of carbon and oxygen, and on top of it a He envelope of mass 10^{-4} M_sComment: 11 pages, 11 figures, accepted for publication in A&

Protoneutron Stars with Kaon Condensation and their Delayed Collapse

Properties of protoneutron stars are discussed in the context of kaon condensation. Thermal and neutrino trapping effects are very important ingredients to study them. By solving the TOV equation, we discuss the static properties of protoneutron stars and the possibility of the delayed collapse during their evolution.Comment: 33pages,15 figures, accepted for publication in Nucl. Phys.

Electricity infrastructure enhancement for the security of supply against coordinated malicious attacks

© 2016 IEEE. The impact of coordinated malicious attacks may be dramatically severe and may yield a wide area blackout. A preventive measure is enhancing the infrastructure through investment. Due to limited budget, a decision making is required to select the best possible options, considering cost/benefit ratio. We designed a time-step simulation framework representing the evolution of post-contingency failures and load/system restoration. System unserved energy is translated into economic losses. Different enhancement options can be compared in terms of benefit (reduction in the cost of unserved energy) and of cost (investments needed) to eventually rank them. The simulation framework also provides a way to derive an optimal lost load recovering strategy to accelerate system restoration. In this paper the simulation framework is applied to a real network (Austrian transmission grid) to evaluate the technical and economic impacts of a coordinated malicious attack

Techno-economic impacts of automatic undervoltage load shedding under emergency

© 2015 Elsevier B.V. All rights reserved. Different schemes for voltage control under emergency are adopted in different jurisdictions around the world. While some features, such as Automatic Voltage Regulation (AVR), are common in all countries, for what concerns undervoltage load shedding (UVLS), to contrast voltage instability or collapse, different schemes are adopted. Most US transmission system operators (TSOs) adopt automatic UVLS schemes, with different capabilities and settings while TSOs in EU usually do not implement automatic UVLS but leave the decisions to the control room operators. The two options may lead to different impacts in terms of trajectory and final status of the transmission grid under emergency, with different unserved energy. In this paper we analyze the impacts from a technical and economic perspective, modeling the grid behavior with different UVLS schemes (none, manual and automatic). The comparison between the different schemes is done resorting to the Incident Response System (IRS), a software tool developed by the authors in the EU-FP7 SESAME project. An illustrative example to a realistic test case is presented and discussed. This paper shows that automatic UVLS is superior to Manual UVLS, from both technical and economic point of view, due to the fast evolution of voltage collapse phenomena and insufficient time for system operators' manual reaction. The benefits of the scheme involving the automatic UVLS can be then compared with the investment costs of equipping the network with those devices