SBNet: Sparse Blocks Network for Fast Inference

Conventional deep convolutional neural networks (CNNs) apply convolution operators uniformly in space across all feature maps for hundreds of layers - this incurs a high computational cost for real-time applications. For many problems such as object detection and semantic segmentation, we are able to obtain a low-cost computation mask, either from a priori problem knowledge, or from a low-resolution segmentation network. We show that such computation masks can be used to reduce computation in the high-resolution main network. Variants of sparse activation CNNs have previously been explored on small-scale tasks and showed no degradation in terms of object classification accuracy, but often measured gains in terms of theoretical FLOPs without realizing a practical speed-up when compared to highly optimized dense convolution implementations. In this work, we leverage the sparsity structure of computation masks and propose a novel tiling-based sparse convolution algorithm. We verified the effectiveness of our sparse CNN on LiDAR-based 3D object detection, and we report significant wall-clock speed-ups compared to dense convolution without noticeable loss of accuracy.Comment: 10 pages, CVPR 201

Exploiting Sparse Semantic HD Maps for Self-Driving Vehicle Localization

In this paper we propose a novel semantic localization algorithm that exploits multiple sensors and has precision on the order of a few centimeters. Our approach does not require detailed knowledge about the appearance of the world, and our maps require orders of magnitude less storage than maps utilized by traditional geometry- and LiDAR intensity-based localizers. This is important as self-driving cars need to operate in large environments. Towards this goal, we formulate the problem in a Bayesian filtering framework, and exploit lanes, traffic signs, as well as vehicle dynamics to localize robustly with respect to a sparse semantic map. We validate the effectiveness of our method on a new highway dataset consisting of 312km of roads. Our experiments show that the proposed approach is able to achieve 0.05m lateral accuracy and 1.12m longitudinal accuracy on average while taking up only 0.3% of the storage required by previous LiDAR intensity-based approaches.Comment: 8 pages, 4 figures, 4 tables, 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2019

Elastic theory of flux lattices in presence of weak disorder

The effect of disorder on flux lattices at equilibrium is studied quantitatively in the absence of free dislocations using both the Gaussian variational method and the renormalization group. Our results for the mean square relative displacements clarify the nature of the crossovers with distance. We find three regimes: (i) a short distance regime (``Larkin regime'') where elasticity holds (ii) an intermediate regime (``Random Manifold'') where vortices are pinned independently (iii) a large distance, quasi-ordered regime where the periodicity of the lattice becomes important and there is universal logarithmic growth of displacements for $2<d<4$ and persistence of algebraic quasi-long range translational order. The functional renormalization group to $O(\epsilon=4-d)$ and the variational method, agree within $10\%$ on the value of the exponent. In $d=3$ we compute the crossover function between the three regimes. We discuss the observable signature of this crossover in decoration experiments and in neutron diffraction experiments on flux lattices. Qualitative arguments are given suggesting the existence for weak disorder in $d=3$ of a `` Bragg glass '' phase without free dislocations and with algebraically divergent Bragg peaks. In $d=1+1$ both the variational method and the Cardy-Ostlund renormalization group predict a glassy state below the same transition temperature $T=T_c$, but with different behaviors. Applications to $d=2+0$ systems and experiments on magnetic bubbles are discussed.Comment: 59 pages; RevTeX 3.0; 5 postscript figures uuencode

Moving glass theory of driven lattices with disorder

We study periodic structures, such as vortex lattices, moving in a random potential. As predicted in [T. Giamarchi, P. Le Doussal Phys. Rev. Lett. 76 3408 (1996)] the periodicity in the direction transverse to motion leads to a new class of driven systems: the Moving Glasses. We analyse using several RG techniques the properties at T=0 and $T>0$: (i) decay of translational long range order (ii) particles flow along static channels (iii) the channel pattern is highly correlated (iv) barriers to transverse motion. We demonstrate the existence of the ``transverse critical force'' at T=0. A ``static random force'' is shown to be generated by motion. Displacements grow logarithmically in $d=3$ and algebraically in $d=2$. The persistence of quasi long range translational order in $d=3$ at weak disorder, or large velocity leads to predict a topologically ordered ``Moving Bragg Glass''. This state continues the static Bragg glass and is stable at $T>0$, with non linear transverse response and linear asymptotic behavior. In $d=2$, or in $d=3$ at intermediate disorder, another moving glass exist (the Moving Transverse Glass) with smectic quasi order in the transverse direction. A phase diagram in $T$ force and disorder for static and moving structures is proposed. For correlated disorder we predict a ``moving Bose glass'' state with anisotropic transverse Meissner effect and transverse pinning. We discuss experimental consequences such as anomalous Hall effect in Wigner crystal and transverse critical current in vortex lattice.Comment: 74 pages, 27 figures, RevTe

Biological Earth observation with animal sensors

Space-based tracking technology using low-cost miniature tags is now delivering data on fine-scale animal movement at near-global scale. Linked with remotely sensed environmental data, this offers a biological lens on habitat integrity and connectivity for conservation and human health; a global network of animal sentinels of environmen-tal change

Extreme biomimetics: Preservation of molecular detail in centimeter-scale samples of biological meshes laid down by sponges

International audienceFabrication of biomimetic materials and scaffolds is usually a micro- or even nanoscale process; however, most testing and all manufacturing require larger-scale synthesis of nanoscale features. Here, we propose the utilization of naturally prefabricated three-dimensional (3D) spongin scaffolds that preserve molecular detail across centimeter-scale samples. The fine-scale structure of this collagenous resource is stable at temperatures of up to 1200°C and can produce up to 4 × 10–cm–large 3D microfibrous and nanoporous turbostratic graphite. Our findings highlight the fact that this turbostratic graphite is exceptional at preserving the nanostructural features typical for triple-helix collagen. The resulting carbon sponge resembles the shape and unique microarchitecture of the original spongin scaffold. Copper electroplating of the obtained composite leads to a hybrid material with excellent catalytic performance with respect to the reduction of p-nitrophenol in both freshwater and marine environments

Tunable Plasmonic Properties and Absorption Enhancement in Terahertz Photoconductive Antenna Based on Optimized Plasmonic Nanostructures

Herein, we numerically investigate terahertz photoconductive antennas (PCAs) based on optimized plasmonic nanostructures and absorption enhancement in nanocylinders. Plasmonic behavior in the visible to near-infrared light spectrum is achievable due to the metallic nanostructure employment. Herein, we study the absorption enhancement of silver and transparent-conducting oxides (TCO) nanocylinders with different diameters by means of effective medium approximation. This study also reports on the stronger enhancement in the case of TCO nanocylinders. The results show that resonant absorption amplitude and wavelength are dramatically affected by the thickness of the nanostructure as well as by the distances between nanocylinders. The outputs reported here provide a fertile ground for precise control of the nanowire structures for sensing and other enhanced optical applications. It is worthwhile noting that in case of TCO nanocylinders, absorption enhancement for NIR wavelengths, being relevant for present terahertz generation setup, reaches up to fivefold leading to 25-fold increase in terahertz radiation