17,903 research outputs found

    Learning a Hierarchical Latent-Variable Model of 3D Shapes

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    We propose the Variational Shape Learner (VSL), a generative model that learns the underlying structure of voxelized 3D shapes in an unsupervised fashion. Through the use of skip-connections, our model can successfully learn and infer a latent, hierarchical representation of objects. Furthermore, realistic 3D objects can be easily generated by sampling the VSL's latent probabilistic manifold. We show that our generative model can be trained end-to-end from 2D images to perform single image 3D model retrieval. Experiments show, both quantitatively and qualitatively, the improved generalization of our proposed model over a range of tasks, performing better or comparable to various state-of-the-art alternatives.Comment: Accepted as oral presentation at International Conference on 3D Vision (3DV), 201

    DecideNet: Counting Varying Density Crowds Through Attention Guided Detection and Density Estimation

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    In real-world crowd counting applications, the crowd densities vary greatly in spatial and temporal domains. A detection based counting method will estimate crowds accurately in low density scenes, while its reliability in congested areas is downgraded. A regression based approach, on the other hand, captures the general density information in crowded regions. Without knowing the location of each person, it tends to overestimate the count in low density areas. Thus, exclusively using either one of them is not sufficient to handle all kinds of scenes with varying densities. To address this issue, a novel end-to-end crowd counting framework, named DecideNet (DEteCtIon and Density Estimation Network) is proposed. It can adaptively decide the appropriate counting mode for different locations on the image based on its real density conditions. DecideNet starts with estimating the crowd density by generating detection and regression based density maps separately. To capture inevitable variation in densities, it incorporates an attention module, meant to adaptively assess the reliability of the two types of estimations. The final crowd counts are obtained with the guidance of the attention module to adopt suitable estimations from the two kinds of density maps. Experimental results show that our method achieves state-of-the-art performance on three challenging crowd counting datasets.Comment: CVPR 201

    To be or not to be intrusive? The solution of parametric and stochastic equations - the "plain vanilla" Galerkin case

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    In parametric equations - stochastic equations are a special case - one may want to approximate the solution such that it is easy to evaluate its dependence of the parameters. Interpolation in the parameters is an obvious possibility, in this context often labeled as a collocation method. In the frequent situation where one has a "solver" for the equation for a given parameter value - this may be a software component or a program - it is evident that this can independently solve for the parameter values to be interpolated. Such uncoupled methods which allow the use of the original solver are classed as "non-intrusive". By extension, all other methods which produce some kind of coupled system are often - in our view prematurely - classed as "intrusive". We show for simple Galerkin formulations of the parametric problem - which generally produce coupled systems - how one may compute the approximation in a non-intusive way

    Filamentous Connections between Ediacaran Fronds.

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    Fossils of the Ediacaran macrobiota (∼571-539 mya) record phylogenetically diverse marine palaeocommunities, including early animals, which pre-date the "Cambrian Explosion" [1-4]. Benthic forms with a frondose gross morphology, assigned to the morphogroups Rangeomorpha [5] and Frondomorpha (see also Arboreomorpha) [6-8], are among the most temporally wide-ranging and environmentally tolerant members of the Ediacaran macrobiota [6] and dominated deep-marine ecosystems ∼571-560 mya [9-11]. Investigations into the morphology [12-14], palaeoecology [10, 15, 16], reproductive strategies [17, 18], feeding methods [9, 19], and morphogenesis of frondose taxa together constrain their phylogenetic position to the metazoan (for Rangeomorpha) or eumetazoan (e.g., Arborea) total groups [14, 20], but tighter constraint is currently lacking. Here, we describe fossils of abundant filamentous organic structures preserved among frond-dominated fossil assemblages in Newfoundland (Canada). The filaments constitute a prominent component of the ecosystems, and exhibit clear physical associations with at least seven frondose taxa. Individual specimens of one uniterminal rangeomorph taxon appear to be directly connected by filaments across distances of centimeters to meters. Such physical linkages are interpreted to reflect evidence for stolonic connections: a conclusion with potential implications for the phylogenetic placement and palaeoecology of frondose organisms. Consideration of extant stoloniferous organisms suggests that Ediacaran frondose taxa were likely clonal and resurrects the possibility that they may have been colonial (e.g., [21, 22]). VIDEO ABSTRACT.NERC National Geographic Geological Society of London Cambridge Philosophical Societ

    Animal Evolution: Only Rocks Can Set the Clock

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    Molecular clocks have become the method of choice to date the tree of life. A new study demonstrates that there are limits to their precision, which may only be overcome by improving our knowledge of the fossil record

    Hidden magnetic order in CuNCN

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    We report a comprehensive experimental and theoretical study of the quasi-one-dimensional quantum magnet CuNCN. Based on magnetization measurements above room temperature as well as muon spin rotation and electron spin resonance measurements, we unequivocally establish the localized Cu+2-based magnetism and the magnetic transition around 70 K, both controversially discussed in the previous literature. Thermodynamic data conform to the uniform-spin-chain model with a nearest-neighbor intrachain coupling of about 2300 K, in remarkable agreement with the microscopic magnetic model based on density functional theory band-structure calculations. Using exact diagonalization and the coupled-cluster method, we derive a collinear antiferromagnetic order with a strongly reduced ordered moment of about 0.4 mu_B, indicating strong quantum fluctuations inherent to this quasi-one-dimensional spin system. We re-analyze the available neutron-scattering data, and conclude that they are not sufficient to resolve or disprove the magnetic order in CuNCN. By contrast, spectroscopic techniques indeed show signatures of long-range magnetic order below 70 K, yet with a rather broad distribution of internal field probed by implanted muons. We contemplate the possible structural origin of this effect and emphasize peculiar features of the microstructure studied with synchrotron powder x-ray diffraction.Comment: 17 pages, 17 figures, 1 tabl

    Interaction-induced mode switching in steady-state microlasers

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    We demonstrate that due to strong modal interactions through cross-gain saturation, the onset of a new lasing mode can switch off an existing mode via a negative power slope. In this process of interaction-induced mode switching (IMS) the two involved modes maintain their identities, i.e. they do not change their spatial field patterns or lasing frequencies. For a fixed pump profile, a simple analytic criterion for the occurrence of IMS is given in terms of their self- and cross-interaction coefficients and non-interacting thresholds, which is verified for the example of a two-dimensional microdisk laser. When the spatial pump profile is varied as the pump power is increased, IMS can be induced even when it would not occur with a fixed pump profile, as we show for two coupled laser cavities. Our findings apply to steady-state lasing and are hence different from dynamical mode switching or hopping. IMS may have potential applications in robust and flexible all-optical switching.Comment: 14 pages, 5 figure
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