Summarizing First-Person Videos from Third Persons' Points of Views

Video highlight or summarization is among interesting topics in computer vision, which benefits a variety of applications like viewing, searching, or storage. However, most existing studies rely on training data of third-person videos, which cannot easily generalize to highlight the first-person ones. With the goal of deriving an effective model to summarize first-person videos, we propose a novel deep neural network architecture for describing and discriminating vital spatiotemporal information across videos with different points of view. Our proposed model is realized in a semi-supervised setting, in which fully annotated third-person videos, unlabeled first-person videos, and a small number of annotated first-person ones are presented during training. In our experiments, qualitative and quantitative evaluations on both benchmarks and our collected first-person video datasets are presented.Comment: 16+10 pages, ECCV 201

MOON: A Mixed Objective Optimization Network for the Recognition of Facial Attributes

Attribute recognition, particularly facial, extracts many labels for each image. While some multi-task vision problems can be decomposed into separate tasks and stages, e.g., training independent models for each task, for a growing set of problems joint optimization across all tasks has been shown to improve performance. We show that for deep convolutional neural network (DCNN) facial attribute extraction, multi-task optimization is better. Unfortunately, it can be difficult to apply joint optimization to DCNNs when training data is imbalanced, and re-balancing multi-label data directly is structurally infeasible, since adding/removing data to balance one label will change the sampling of the other labels. This paper addresses the multi-label imbalance problem by introducing a novel mixed objective optimization network (MOON) with a loss function that mixes multiple task objectives with domain adaptive re-weighting of propagated loss. Experiments demonstrate that not only does MOON advance the state of the art in facial attribute recognition, but it also outperforms independently trained DCNNs using the same data. When using facial attributes for the LFW face recognition task, we show that our balanced (domain adapted) network outperforms the unbalanced trained network.Comment: Post-print of manuscript accepted to the European Conference on Computer Vision (ECCV) 2016 http://link.springer.com/chapter/10.1007%2F978-3-319-46454-1_

Comparison of various lazaroid compounds for protection against ischemic liver injury

Lazaroids are a group of 21-aminosteroids that lack steroid action but have a potent cytoprotective effect by inhibiting iron-dependent lipid peroxidation. However, there have been conflicting reports on the effectiveness and potency of the various lazaroid compounds. In this study, we compared the effectiveness of three major lazaroids on warm liver ischemia in dogs using a 2-hr hepatic vascular exclusion model. The agents were given to the animals intravenously for 30 min before ischemia. The animals were divided into 5 groups: Control (n=10), no treatment; Group F (n=6), U-74006F (10 mg/kg); Group G (n=6), U-74389G (10 mg/kg); Group A1 (n=6), U-74500A (10 mg/kg); Group A2 (n=6), U-74500A (5 mg/kg). The effect of treatment was evaluated by two-week animal survival, hepatic tissue blood flow, liver function tests, blood and tissue biochemistry, and histological analyses. Animal survival in all treated groups was significantly improved compared with the control (83-100% versus 30%). Elevation of liver enzymes after reperfusion was markedly attenuated in treated groups, except for an early significant increase in Group G. Postreperfusion hepatic tissue blood flow was much higher in all treated animals (50% of the preischemic level vs. 25% in the control). Lazaroids, particularly U-74500A at 5 mg/kg (Group A2), suppressed adenine nucleotide degradation during ischemia and enhanced the resynthesis of high-energy phosphates after reperfusion. Although structural abnormalities in postreperfusion liver tissues were markedly ameliorated in all treated groups, Group A2 showed significantly less neutrophil infiltration. Liver injury from warm ischemia and reperfusion was attenuated with all lazaroid compounds, of which U-74500A at 5 mg/kg exhibited the most significant protective activity

Effect of pH and temperature on the morphology and phases of co-precipitated hydroxyapatite

This paper reports a high-yield process to fabricate biomimetic hydroxyapatite nano-particles or nano-plates. Hydroxyapatite is obtained by simultaneous dripping of calcium chloride and ammonium hydrogen phosphate solutions into a reaction vessel. Reactions were carried out under various pH and temperature conditions. The morphology and phase composition of the precipitates were investigated using scanning electron microscope and X-ray diffraction. The analyses showed that large plates of calcium hydrophosphate are formed at neutral or acidic pH condition. Nanoparticles of hydroxyapatite were obtained in precipitates prepared at pH 9–11. Hydroxyapatite plates akin to seashell nacre were obtained at 40 °C and pH 9. This material holds promise to improve the strength of hydroxyapatite containing composites for bone implant or bone cement used in orthopaedic surgeries. The thermodynamics of the crystal growth under these conditions was discussed. An assembly mechanism of the hydroxyapatite plates was proposed according to the nanostructure observations

Reducing combinatorial uncertainties: A new technique based on MT2 variables

We propose a new method to resolve combinatorial ambiguities in hadron collider events involving two invisible particles in the final state. This method is based on the kinematic variable MT2 and on the MT2-assisted-on-shell reconstruction of invisible momenta, that are reformulated as `test' variables Ti of the correct combination against the incorrect ones. We show how the efficiency of the single Ti in providing the correct answer can be systematically improved by combining the different Ti and/or by introducing cuts on suitable, combination-insensitive kinematic variables. We illustrate our whole approach in the specific example of top anti-top production, followed by a leptonic decay of the W on both sides. However, by construction, our method is also directly applicable to many topologies of interest for new physics, in particular events producing a pair of undetected particles, that are potential dark-matter candidates. We finally emphasize that our method is apt to several generalizations, that we outline in the last sections of the paper.Comment: 1+23 pages, 8 figures. Main changes in v3: (1) discussion at the end of sec. 2 improved; (2) added sec. 4.2 about the method's dependence on mass information. Matches journal versio

Gate-Controlled Ionization and Screening of Cobalt Adatoms on a Graphene Surface

We describe scanning tunneling spectroscopy (STS) measurements performed on individual cobalt (Co) atoms deposited onto backgated graphene devices. We find that Co adatoms on graphene can be ionized by either the application of a global backgate voltage or by the application of a local electric field from a scanning tunneling microscope (STM) tip. Large screening clouds are observed to form around Co adatoms ionized in this way, and we observe that some intrinsic graphene defects display a similar behavior. Our results provide new insight into charged impurity scattering in graphene, as well as the possibility of using graphene devices as chemical sensors.Comment: 19 pages, 4 figure

First direct observation of Dirac fermions in graphite

Originating from relativistic quantum field theory, Dirac fermions have been recently applied to study various peculiar phenomena in condensed matter physics, including the novel quantum Hall effect in graphene, magnetic field driven metal-insulator-like transition in graphite, superfluid in 3He, and the exotic pseudogap phase of high temperature superconductors. Although Dirac fermions are proposed to play a key role in these systems, so far direct experimental evidence of Dirac fermions has been limited. Here we report the first direct observation of massless Dirac fermions with linear dispersion near the Brillouin zone (BZ) corner H in graphite, coexisting with quasiparticles with parabolic dispersion near another BZ corner K. In addition, we report a large electron pocket which we attribute to defect-induced localized states. Thus, graphite presents a novel system where massless Dirac fermions, quasiparticles with finite effective mass, and defect states all contribute to the low energy electronic dynamics.Comment: Nature Physics, in pres

Past Achievements and Future Challenges in 3D Photonic Metamaterials

Photonic metamaterials are man-made structures composed of tailored micro- or nanostructured metallo-dielectric sub-wavelength building blocks that are densely packed into an effective material. This deceptively simple, yet powerful, truly revolutionary concept allows for achieving novel, unusual, and sometimes even unheard-of optical properties, such as magnetism at optical frequencies, negative refractive indices, large positive refractive indices, zero reflection via impedance matching, perfect absorption, giant circular dichroism, or enhanced nonlinear optical properties. Possible applications of metamaterials comprise ultrahigh-resolution imaging systems, compact polarization optics, and cloaking devices. This review describes the experimental progress recently made fabricating three-dimensional metamaterial structures and discusses some remaining future challenges