Adversarially Tuned Scene Generation

Generalization performance of trained computer vision systems that use computer graphics (CG) generated data is not yet effective due to the concept of 'domain-shift' between virtual and real data. Although simulated data augmented with a few real world samples has been shown to mitigate domain shift and improve transferability of trained models, guiding or bootstrapping the virtual data generation with the distributions learnt from target real world domain is desired, especially in the fields where annotating even few real images is laborious (such as semantic labeling, and intrinsic images etc.). In order to address this problem in an unsupervised manner, our work combines recent advances in CG (which aims to generate stochastic scene layouts coupled with large collections of 3D object models) and generative adversarial training (which aims train generative models by measuring discrepancy between generated and real data in terms of their separability in the space of a deep discriminatively-trained classifier). Our method uses iterative estimation of the posterior density of prior distributions for a generative graphical model. This is done within a rejection sampling framework. Initially, we assume uniform distributions as priors on the parameters of a scene described by a generative graphical model. As iterations proceed the prior distributions get updated to distributions that are closer to the (unknown) distributions of target data. We demonstrate the utility of adversarially tuned scene generation on two real-world benchmark datasets (CityScapes and CamVid) for traffic scene semantic labeling with a deep convolutional net (DeepLab). We realized performance improvements by 2.28 and 3.14 points (using the IoU metric) between the DeepLab models trained on simulated sets prepared from the scene generation models before and after tuning to CityScapes and CamVid respectively.Comment: 9 pages, accepted at CVPR 201

Low-Alloy High-Strength Steels

IT is significant that this symposium on alloy steels is being held in the year 1956 which marks the centenary of the birth of tonnage steel. It was exactly a hundred years ago that Henry Bessemer heralded it new era by making it possible to produce steel for the first time in commercial tonnages. The largest proportion of steel made and rolled today finds its way into, structural appli-cations such as the building of bridges, transport cars, etc. Therefore structural steel occupies a promin-ent place in the eyes of the metallurgist and the engineer. Although the manufacture of Bessemer steel was well established within a few years of its discovery, the general use of steel in building bridges and other struc-tural uses had to wait for several years. As late as 1877, a Board of Trade Regulation in England prohibited the use of mild steel in bridges. The Firth of Forth Bridge built during 1 2380-1 8 90 used for the first time steel in large quantities. The earliest use of mild steel for bridges in U.S.A. was in the Eads Bridge over the 'Mississippi river. Since then the use of mild steel for bridges has become almost universal

Dolomite as a flux for High-Alumina Blast Furnace Slags

BLAST FURNACE operators at Jamshedpur have to face a peculiar problem arising out of the high concentration of it alumina in the slag. The normal analyses are 37.3-37.8% CaO, 3.4-3.9% MgO,30.4-31.5% SiO2, 26.2-27.0% Al2O3, 0.69-0.78% FeO and 0.69-0.82% S. The actual level, i.e. 26 to 28% is much higher than that common elsewhere and brings into force a series of adverse effects. Briefly, these consist of the greater viscosity of the alumina slags, greater tendency towards silicon reduction, and less efficient desulphurisation. As a result, it becomes rather difficult consistently to produce low-sulphur hot metal without exceeding the silicon level normally specified for basic iron

Optical Polarization of 52 Radio-Loud QSOs and BL Lac Objects

Polarization measurements are presented for 52 radio-loud QSOs and BL Lac objects. For 9 highly polarized (p >3%) AGN, these are the first published polarization measurements. Of these 9, 7 are highly-polarized QSOs (HPQs), one is a BL Lac object and another is a likely BL Lac object. Polarization variability is confirmed for some of these new and previously known highly-polarized AGN. While 6 of the HPQs have flat radio spectra are almost certainly blazars, PKS 1452-217 is probably a new member of the rare class of radio-loud QSOs that show high polarization by scattering, and is therefore important for testing orientation Unified Schemes. In competition for the highest redshift HPQ are the well-observed QSO PKS 0438-43 at z = 2.85, with maximum p = 4.7%, and PKS 0046-315 at z = 2.72, for which we find p = 13%.Comment: 6 pages. Astronomical Journal, in pres

Suppressed star formation in circumnuclear regions in Seyfert galaxies

Feedback from black hole activity is widely believed to play a key role in regulating star formation and black hole growth. A long-standing issue is the relation between the star formation and fueling the supermassive black holes in active galactic nuclei (AGNs). We compile a sample of 57 Seyfert galaxies to tackle this issue. We estimate the surface densities of gas and star formation rates in circumnuclear regions (CNRs). Comparing with the well-known Kennicutt-Schmidt (K-S) law, we find that the star formation rates in CNRs of most Seyfert galaxies are suppressed in this sample. Feedback is suggested to explain the suppressed star formation rates.Comment: 1 color figure and 1 table. ApJ Letters in pres