459,294 research outputs found

    Large-Scale Pedestrian Retrieval Competition

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    The Large-Scale Pedestrian Retrieval Competition (LSPRC) mainly focuses on person retrieval which is an important end application in intelligent vision system of surveillance. Person retrieval aims at searching the interested target with specific visual attributes or images. The low image quality, various camera viewpoints, large pose variations and occlusions in real scenes make it a challenge problem. By providing large-scale surveillance data in real scene and standard evaluation methods that are closer to real application, the competition aims to improve the robust of related algorithms and further meet the complicated situations in real application. LSPRC includes two kinds of tasks, i.e., Attribute based Pedestrian Retrieval (PR-A) and Re-IDentification (ReID) based Pedestrian Retrieval (PR-ID). The normal evaluation index, i.e., mean Average Precision (mAP), is used to measure the performances of the two tasks under various scale, pose and occlusion. While the method of system evaluation is introduced to evaluate the person retrieval system in which the related algorithms of the two tasks are integrated into a large-scale video parsing platform (named ISEE) combing with algorithm of pedestrian detection

    Depth creates no more spurious local minima

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    We show that for any convex differentiable loss, a deep linear network has no spurious local minima as long as it is true for the two layer case. This reduction greatly simplifies the study on the existence of spurious local minima in deep linear networks. When applied to the quadratic loss, our result immediately implies the powerful result in [Kawaguchi 2016]. Further, with the work in [Zhou and Liang 2018], we can remove all the assumptions in [Kawaguchi 2016]. This property holds for more general "multi-tower" linear networks too. Our proof builds on [Laurent and von Brecht 2018] and develops a new perturbation argument to show that any spurious local minimum must have full rank, a structural property which can be useful more generally

    Wilson Line Response of Holographic Superconductors in Gauss-Bonnet Gravity

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    We study the Wilson line response in the holographic superconducting phase transitions in Gauss-Bonnet gravity. In the black brane background case, the Little-Parks periodicity is independent of the Gauss-Bonnet parameter, while in the AdS soliton case, there is no evidence for the Little-Parks periodicity. We further study the impact of the Gauss-Bonnet term on the holographic phase transitions quantitatively. The results show that such quantum corrections can effectively affect the occurrence of the phase transitions and the response to the Wilson line.Comment: 19 pages, 6 figures, 2 tables, references adde

    Multi-window dilation-and-modulation frames on the half real line

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    Wavelet and Gabor systems are based on translation-and-dilation and translation-and-modulation operators, respectively. They have been extensively studied. However, dilation-and-modulation systems have not, and they cannot be derived from wavelet or Gabor systems. In this paper, we investigate a class of dilation-and-modulation systems in the causal signal space L2(R+)L^{2}(\Bbb R_{+}). L2(R+)L^{2}(\Bbb R_{+}) can be identified a subspace of L2(R)L^{2}(\Bbb R) consisting of all L2(R)L^{2}(\Bbb R)-functions supported on R+\Bbb R_{+}, and is unclosed under the Fourier transform. So the Fourier transform method does not work in L2(R+)L^{2}(\Bbb R_{+}). In this paper, we introduce the notion of Θa\Theta_{a}-transform in L2(R+)L^{2}(\Bbb R_{+}), using Θa\Theta_{a}-transform we characterize dilation-and-modulation frames and dual frames in L2(R+)L^{2}(\Bbb R_{+}); and present an explicit expression of all duals with the same structure for a general dilation-and-modulation frame for L2(R+)L^{2}(\Bbb R_{+}). Interestingly, we prove that an arbitrary frame of this form is always nonredundant whenever the number of the generators is 11, and is always redundant whenever it is greater than 11. Some examples are also provided to illustrate the generality of our results

    Models of vacuum energy interacting with cold dark matter: Constraints and comparison

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    In this paper, we investigate the observational constraints on the scenario of vacuum energy interacting with cold dark matter. We consider eight typical interaction forms in such an interacting vacuum energy scenario. The observational data used in this work to constrain these models include the JLA sample of type Ia supernovae observation, the Planck 2015 distance priors data of cosmic microwave background anisotropies observation, the baryon acoustic oscillations data, and the Hubble constant direct measurement. We find that the current observational data almost equally favor these interacting vacuum energy models. We also find that for all these models of vacuum energy interacting with cold dark matter the case of no interaction is actually well consistent with the current observational data within 1σ\sigma range.Comment: 13 pages, 6 figure

    Minimum Enclosing Circle of a Set of Static Points with Dynamic Weight from One Free Point

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    Given a set SS of nn static points and a free point pp in the Euclidean plane, we study a new variation of the minimum enclosing circle problem, in which a dynamic weight that equals to the reciprocal of the distance from the free point pp to the undetermined circle center is included. In this work, we prove the optimal solution of the new problem is unique and lies on the boundary of the farthest-point Voronoi diagram of SS, once pp does not coincide with any vertex of the convex hull of SS. We propose a tree structure constructed from the boundary of the farthest-point Voronoi diagram and use the hierarchical relationship between edges to locate the optimal solution. The plane could be divide into at most 3n−43n-4 non-overlapping regions. When pp lies in one of the regions, the optimal solution locates at one node or lies on the interior of one edge in the boundary of the farthest-point Voronoi diagram. Moreover, we apply the new variation to calculate the maximum displacement of one point pp under the condition that the displacements of points in SS are restricted in 2D rigid motion.Comment: 14 pages, 8 figure

    Multi-Channel Pyramid Person Matching Network for Person Re-Identification

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    In this work, we present a Multi-Channel deep convolutional Pyramid Person Matching Network (MC-PPMN) based on the combination of the semantic-components and the color-texture distributions to address the problem of person re-identification. In particular, we learn separate deep representations for semantic-components and color-texture distributions from two person images and then employ pyramid person matching network (PPMN) to obtain correspondence representations. These correspondence representations are fused to perform the re-identification task. Further, the proposed framework is optimized via a unified end-to-end deep learning scheme. Extensive experiments on several benchmark datasets demonstrate the effectiveness of our approach against the state-of-the-art literature, especially on the rank-1 recognition rate.Comment: 9 pages, 5 figures, 7 tables and accepted by the 32nd AAAI Conference on Artificial Intelligenc

    Generalized Semi-Holographic Universe

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    We study the semi-holographic idea in context of decaying dark components. The energy flow between dark energy and the compensating dark matter is thermodynamically generalized to involve a particle number variable dark component with non-zero chemical potential. It's found that, unlike the original semi-holographic model, no cosmological constant is needed for a dynamical evolution of the universe. A transient phantom phase appears while a non-trivial dark energy-dark matter scaling solution keeps at late time, which evades the big-rip and helps to resolve the coincidence problem. For reasonable parameters, the deceleration parameter is well consistent with current observations. The original semi-holographic model is extended and it also suggests that the concordance model may be reconstructed from the semi-holographic idea.Comment: 15pages,5figs. arXiv admin note: substantial text overlap with arXiv:1010.136

    A mean value formula and a Liouville theorem for the complex Monge-Amp\`ere equation

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    In this paper, we prove a mean value formula for bounded subharmonic Hermitian matrix valued function on a complete Riemannian manifold with nonnegative Ricci curvature. As its application, we obtain a Liouville type theorem for the complex Monge-Amp\`ere equation on product manifolds

    Exponential inequalities under sub-linear expectations with applications to laws of the iterated logarithm

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    Kolmogorov's exponential inequalities are basic tools for studying the strong limit theorems such as the classical laws of the iterated logarithm for both independent and dependent random variables. This paper establishes the Kolmogorov type exponential inequalities of the partial sums of independent random variables as well as negatively dependent random variables under the sub-linear expectations. As applications of the exponential inequalities, the laws of the iterated logarithm in the sense of non-additive capacities are proved for independent or negatively dependent identically distributed random variables with finite second order moments. For deriving a lower bound of an exponential inequality, a central limit theorem is also proved under the sub-linear expectation for random variables with only finite variances.Comment: 30 pages. arXiv admin note: text overlap with arXiv:1408.529
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