Electronic structure of the Ca3Co4O9\rm Ca_3Co_4O_9 compound from ab initio local interactions

We used fully correlated ab initio calculations to determine the effective parameters of Hubbard and t - J models for the thermoelectric misfit compound $\rm Ca_3Co_4O_9$. As for the $\rm Na_xCoO_2$ family the Fermi level orbitals are the $a_{1g}$ orbitals of the cobalt atoms ; the $e'_g$ being always lower in energy by more than 240\,meV. The electron correlation is found very large $U/t\sim 26$ as well as the parameters fluctuations as a function of the structural modulation. The main consequences are a partial $a_{1g}$ electrons localization and a fluctuation of the in-plane magnetic exchange from AFM to FM. The behavior of the Seebeck coefficient as a function of temperature is discussed in view of the ab initio results, as well as the 496\,K phase transition

3D Pose Estimation and 3D Model Retrieval for Objects in the Wild

We propose a scalable, efficient and accurate approach to retrieve 3D models for objects in the wild. Our contribution is twofold. We first present a 3D pose estimation approach for object categories which significantly outperforms the state-of-the-art on Pascal3D+. Second, we use the estimated pose as a prior to retrieve 3D models which accurately represent the geometry of objects in RGB images. For this purpose, we render depth images from 3D models under our predicted pose and match learned image descriptors of RGB images against those of rendered depth images using a CNN-based multi-view metric learning approach. In this way, we are the first to report quantitative results for 3D model retrieval on Pascal3D+, where our method chooses the same models as human annotators for 50% of the validation images on average. In addition, we show that our method, which was trained purely on Pascal3D+, retrieves rich and accurate 3D models from ShapeNet given RGB images of objects in the wild.Comment: Accepted to Conference on Computer Vision and Pattern Recognition (CVPR) 201

The crucial importance of the t2gt_{2g}--ege_g hybridization in transition metal oxides

We studied the influence of the trigonal distortion of the regular octahedron along the (111) direction, found in the $\rm CoO_2$ layers. Under such a distortion the $t_{2g}$ orbitals split into one $a_{1g}$ and two degenerated $e_g^\prime$ orbitals. We focused on the relative order of these orbitals. Using quantum chemical calculations of embedded clusters at different levels of theory, we analyzed the influence of the different effects not taken into account in the crystalline field theory; that is metal-ligand hybridization, long-range crystalline field, screening effects and orbital relaxation. We found that none of them are responsible for the relative order of the $t_{2g}$ orbitals. In fact, the trigonal distortion allows a mixing of the $t_{2g}$ and $e_g$ orbitals of the metallic atom. This hybridization is at the origin of the $a_{1g}$--$e_g^\prime$ relative order and of the incorrect prediction of the crystalline field theory

An ab initio study of magneto-electric coupling of YMnO3\rm YMnO_3

The present paper proposes the direct calculation of the microscopic contributions to the magneto-electric coupling, using ab initio methods. The electrostrictive and the Dzyaloshinskii-Moriya contributions were evaluated individually. For this purpose a specific method was designed, combining DFT calculations and embedded fragments, explicitely correlated, quantum chemical calculations. This method allowed us to calculate the evolution of the magnetic couplings as a function of an applied electric field. We found that in $\rm YMnO_3$ the Dzyaloshinskii-Moriya contribution to the magneto-electric effect is three orders of magnitude weaker than the electrostrictive contribution. Strictive effects are thus dominant in the magnetic exchange evolution under an applied electric field, and by extension on the magneto-electric effect. These effects remain however quite small and the modifications of the magnetic excitations under an applied electric field will be difficult to observe experimentally. Another important conclusion is that the amplitude of the magneto-electric effect is very small. Indeed, it can be shown that the linear magneto-electric tensor is null due to the inter-layer symmetry operations.Comment: J. Phys. Cond. Matter 201

Sr_14Cu_24O_41Sr\_{14}Cu\_{24}O\_{41} : a complete model for the chain sub-system

A second neighbor $t-J+V$ model for the chain subsystem of the $Sr\_{14}Cu\_{24}O\_{41}$ has been extracted from ab-initio calculations. This model does not use periodic approximation but describes the entire chain through the use of the four-dimensional crystallographic description. Second neighbors interactions are found to be of same order than the first neighbors ones. The computed values of the second neighbors magnetic interaction are coherent with experimental estimations of the intra-dimer magnetic interactions, even if slightly smaller. The reasons of this underestimation are detailed. The computed model allowed us to understand the origin of the chain dimerisation and predicts correctly the relative occurrence of dimers and free spins. The orbitals respectively supporting the magnetic electrons and the holes have been found to be essentially supported by the copper 3d orbitals (spins) and the surrounding oxygen $2p$ orbitals (holes), thus giving a strong footing to the existence of Zhang-Rice singlets

GP2C: Geometric Projection Parameter Consensus for Joint 3D Pose and Focal Length Estimation in the Wild

We present a joint 3D pose and focal length estimation approach for object categories in the wild. In contrast to previous methods that predict 3D poses independently of the focal length or assume a constant focal length, we explicitly estimate and integrate the focal length into the 3D pose estimation. For this purpose, we combine deep learning techniques and geometric algorithms in a two-stage approach: First, we estimate an initial focal length and establish 2D-3D correspondences from a single RGB image using a deep network. Second, we recover 3D poses and refine the focal length by minimizing the reprojection error of the predicted correspondences. In this way, we exploit the geometric prior given by the focal length for 3D pose estimation. This results in two advantages: First, we achieve significantly improved 3D translation and 3D pose accuracy compared to existing methods. Second, our approach finds a geometric consensus between the individual projection parameters, which is required for precise 2D-3D alignment. We evaluate our proposed approach on three challenging real-world datasets (Pix3D, Comp, and Stanford) with different object categories and significantly outperform the state-of-the-art by up to 20% absolute in multiple different metrics.Comment: Accepted to International Conference on Computer Vision (ICCV) 201

Location Field Descriptors: Single Image 3D Model Retrieval in the Wild

We present Location Field Descriptors, a novel approach for single image 3D model retrieval in the wild. In contrast to previous methods that directly map 3D models and RGB images to an embedding space, we establish a common low-level representation in the form of location fields from which we compute pose invariant 3D shape descriptors. Location fields encode correspondences between 2D pixels and 3D surface coordinates and, thus, explicitly capture 3D shape and 3D pose information without appearance variations which are irrelevant for the task. This early fusion of 3D models and RGB images results in three main advantages: First, the bottleneck location field prediction acts as a regularizer during training. Second, major parts of the system benefit from training on a virtually infinite amount of synthetic data. Finally, the predicted location fields are visually interpretable and unblackbox the system. We evaluate our proposed approach on three challenging real-world datasets (Pix3D, Comp, and Stanford) with different object categories and significantly outperform the state-of-the-art by up to 20% absolute in multiple 3D retrieval metrics.Comment: Accepted to International Conference on 3D Vision (3DV) 2019 (Oral