6D Object Pose Estimation without PnP

In this paper, we propose an efficient end-to-end algorithm to tackle the problem of estimating the 6D pose of objects from a single RGB image. Our system trains a fully convolutional network to regress the 3D rotation and the 3D translation in region layer. On this basis, a special layer, Collinear Equation Layer, is added next to region layer to output the 2D projections of the 3D bounding boxs corners. In the back propagation stage, the 6D pose network are adjusted according to the error of the 2D projections. In the detection phase, we directly output the position and pose through the region layer. Besides, we introduce a novel and concise representation of 3D rotation to make the regression more precise and easier. Experiments show that our method outperforms base-line and state of the art methods both at accuracy and efficiency. In the LineMod dataset, our algorithm achieves less than 18 ms/object on a GeForce GTX 1080Ti GPU, while the translational error and rotational error are less than 1.67 cm and 2.5 degree

Enhancing and suppressing radiation with some permeability-near-zero structures

Using some special properties of a permeability-near-zero material, the radiation of a line current is greatly enhanced by choosing appropriately the dimension of a dielectric domain in which the source lies and that of a permeability-near-zero shell. The radiation of the source can also be completely suppressed by adding appropriately another dielectric domain or an arbitrary perfect electric conductor (PEC) inside the shell. Enhanced directive radiation is also demonstrated by adding a PEC substrate.Comment: 6 pages, 5 figure

High-subwavelength-resolution imaging of multilayered structures consisting of alternating negative-permittivty and dielectric layers with flattened transmission curves

Multilayered structures consisting of alternating negative-permittivity and dielectric layers are explored to obtain high-resolution imaging of subwavelength objects. The peaks with the smallest |ky| (ky is the transverse wave vector) on the transmission curves, which come from the guided modes of the multilayered structures, can not be completely damped by material loss. This makes the amplitudes of the evanescent waves around these peaks inappropriate after transmitted through the imaging structures, and the imaging quality is not good. To solve such a problem, the permittivity of the dielectric layers is appropriately chosen to make these sharp peaks merge with their neighboring peaks. Wide flat upheavals are then generated on the transmission curves so that evanescent waves in a large range are transmitted through the structures with appropriate amplitudes. In addition, it is found that the sharp peaks with the smallest |ky| can be eliminated by adding appropriate coating layers and wide flat upheavals can also be obtained.Comment: 26 pages, 6 figure

All-Optical Control of Light Group Velocity with a Cavity Optomechanical System

We theoretically demonstrate complete all-optical control of light group velocity via a cavity optomechanical system composed of an optical cavity and a mechanical resonator. The realization depends on no specific materials inside the cavity, and the control of light group velocity stems from the interaction between the signal light and the moving optical diffraction grating within the cavity in analogy to the stimulated Brillouin scattering(SBS). Furthermore, we show that a tunable switch from slow light to fast light can be achieved only by simply adjusting the pump-cavity detuning. The scheme proposed here will open a novel way to control light velocity by all-optical methods in optomechanical systems

Persisting of Polar Distortion with Electron Doping in Lone-Pair Driven Ferroelectrics

Free electrons can screen out long-range Coulomb interaction and destroy the polar distortion in some ferroelectric materials, whereas the coexistence of polar distortion and metallicity were found in several non-central-symmetric metals (NCSMs). Therefore, the mechanisms and designing of NCSMs have attracted great interests. In this work, by first-principles calculation, we found the polar distortion in the lone-pair driven ferroelectric material PbTiO$_3$ can not only persist, but also increase with electron doping. We further analyzed the mechanisms of the persisting of the polar distortion. We found that the Ti site polar instability is suppressed but the Pb site polar instability is intact with the electron doping. The Pb-site instability is due to the lone-pair mechanism which can be viewed as a pseudo-Jahn-Teller effect, a mix of the ground state and the excited state by ion displacement from the central symmetric position. The lone-pair mechanism is not strongly affected by the electron doping because neither the ground state or the excited state involved is at the Fermi energy. The enhancement of the polar distortion is related to the increasing of the Ti ion size by doping. These results show the lone-pair stereoactive ions can be used in designing NCSMs.Comment: 9 pages, 7 figure

Engineering charge ordering into multiferroicity

Multiferroic materials have attracted great interests but are rare in nature. In many transitional metal oxides, charge ordering and magnetic ordering coexist, so that a method of engineering charge-ordered materials into ferroelectric materials would lead to a large class of multiferroic materials. We propose a strategy for designing new ferroelectric or even multiferroic materials by inserting a spacing layer into each two layers of charge-ordered materials and artificially making a superlattice. One example of the model demonstrated here is the perovskite (LaFeO$_3$)$_2$/LaTiO$_3$ (111) superlattice, in which the LaTiO$_3$ layer acts as the donor and the spacing layer, and the LaFeO$_3$ layer is half doped and performs charge ordering. The collaboration of the charge ordering and the spacing layer breaks the space inversion symmetry, resulting in a large ferroelectric polarization. As the charge ordering also leads to a ferrimagnetic structure, the (LaFeO$_3$)$_2$/LaTiO$_3$ is multiferroic. It is expected that this work can encourage the designing and experimentally implementation of a large class of multiferroic structures with novel properties

Well-posedness and scattering for the Boltzmann equations: Soft potential with cut-off

We prove the global existence of the unique mild solution for the Cauchy problem of the cut-off Boltzmann equation for soft potential model $\gamma=2-N$ with initial data small in $L^N_{x,v}$ where $N=2,3$ is the dimension. The proof relies on the existing inhomogeneous Strichartz estimates for the kinetic equation by Ovcharov and convolution-like estimates for the gain term of the Boltzmann collision operator by Alonso, Carneiro and Gamba. The global dynamics of the solution is also characterized by showing that the small global solution scatters with respect to the kinetic transport operator in $L^N_{x,v}$. Also the connection between function spaces and cut-off soft potential model $-N<\gamma<2-N$ is characterized in the local well-posedness result for the Cauchy problem with large initial data.Comment: 12 page

Identification of hybrid node and link communities in complex networks

Identification of communities in complex networks has become an effective means to analysis of complex systems. It has broad applications in diverse areas such as social science, engineering, biology and medicine. Finding communities of nodes and finding communities of links are two popular schemes for network structure analysis. These schemes, however, have inherent drawbacks and are often inadequate to properly capture complex organizational structures in real networks. We introduce a new scheme and effective approach for identifying complex network structures using a mixture of node and link communities, called hybrid node-link communities. A central piece of our approach is a probabilistic model that accommodates node, link and hybrid node-link communities. Our extensive experiments on various real-world networks, including a large protein-protein interaction network and a large semantic association network of commonly used words, illustrated that the scheme for hybrid communities is superior in revealing network characteristics. Moreover, the new approach outperformed the existing methods for finding node or link communities separately.Comment: 22 pages, 8 figures. arXiv admin note: text overlap with arXiv:1105.0257 by other author

Structure Learning in Bayesian Networks of Moderate Size by Efficient Sampling

We study the Bayesian model averaging approach to learning Bayesian network structures (DAGs) from data. We develop new algorithms including the first algorithm that is able to efficiently sample DAGs according to the exact structure posterior. The DAG samples can then be used to construct estimators for the posterior of any feature. We theoretically prove good properties of our estimators and empirically show that our estimators considerably outperform the estimators from the previous state-of-the-art methods.Comment: 51 page

Phase Diagram of Neutron-Proton Condensate in Asymmetric Nuclear Matter

We investigate the phase structure of homogeneous and inhomogeneous neutron-proton condensate in isospin asymmetric nuclear matter. At extremely low nuclear density the condensed matter is in homogeneous phase at any temperature, while in general case it is in Larkin-Ovchinnikov-Fulde -Ferrell phase at low temperature. In comparison with the homogeneous superfluid, the inhomogeneous superfluid can survive at higher nuclear density and higher isospin asymmetry.Comment: 4 pages, 2 figures, arguments and Fig.2 changed, references adde