55 research outputs found
A Deep Primal-Dual Network for Guided Depth Super-Resolution
In this paper we present a novel method to increase the spatial resolution of
depth images. We combine a deep fully convolutional network with a non-local
variational method in a deep primal-dual network. The joint network computes a
noise-free, high-resolution estimate from a noisy, low-resolution input depth
map. Additionally, a high-resolution intensity image is used to guide the
reconstruction in the network. By unrolling the optimization steps of a
first-order primal-dual algorithm and formulating it as a network, we can train
our joint method end-to-end. This not only enables us to learn the weights of
the fully convolutional network, but also to optimize all parameters of the
variational method and its optimization procedure. The training of such a deep
network requires a large dataset for supervision. Therefore, we generate
high-quality depth maps and corresponding color images with a physically based
renderer. In an exhaustive evaluation we show that our method outperforms the
state-of-the-art on multiple benchmarks.Comment: BMVC 201
Pseudo Flow Consistency for Self-Supervised 6D Object Pose Estimation
Most self-supervised 6D object pose estimation methods can only work with
additional depth information or rely on the accurate annotation of 2D
segmentation masks, limiting their application range. In this paper, we propose
a 6D object pose estimation method that can be trained with pure RGB images
without any auxiliary information. We first obtain a rough pose initialization
from networks trained on synthetic images rendered from the target's 3D mesh.
Then, we introduce a refinement strategy leveraging the geometry constraint in
synthetic-to-real image pairs from multiple different views. We formulate this
geometry constraint as pixel-level flow consistency between the training images
with dynamically generated pseudo labels. We evaluate our method on three
challenging datasets and demonstrate that it outperforms state-of-the-art
self-supervised methods significantly, with neither 2D annotations nor
additional depth images.Comment: Accepted by ICCV 202
Semi-Supervised Semantic Segmentation with Pixel-Level Contrastive Learning from a Class-wise Memory Bank
This work presents a novel approach for semi-supervised semantic segmentation. The key element of this approach is our contrastive learning module that enforces the segmentation network to yield similar pixel-level feature representations for same-class samples across the whole dataset. To achieve this, we maintain a memory bank continuously updated with relevant and high-quality feature vectors from labeled data. In an end-to-end training, the features from both labeled and unlabeled data are optimized to be similar to same-class samples from the memory bank. Our approach outperforms the current state-of-the-art for semi-supervised semantic segmentation and semi-supervised domain adaptation on well-known public benchmarks, with larger improvements on the most challenging scenarios, i.e., less available labeled data
The surface-associated exopolysaccharide of Bifidobacterium longum 35624 plays an essential role in dampening host proinflammatory responses and repressing local TH17 responses
The immune-modulating properties of certain bifidobacterial strains, such as Bifidobacterium longum subsp. longum 35624 (B. longum 35624), have been well described, although the strain-specific molecular characteristics associated with such immune-regulatory activity are not well defined. It has previously been demonstrated that B. longum 35624 produces a cell surface exopolysaccharide (sEPS), and in this study, we investigated the role played by this exopolysaccharide in influencing the host immune response. B. longum 35624 induced relatively low levels of cytokine secretion from human dendritic cells, whereas an isogenic exopolysaccharide-negative mutant derivative (termed sEPSneg) induced vastly more cytokines, including interleukin-17 (IL-17), and this response was reversed when exopolysaccharide production was restored in sEPSneg by genetic complementation. Administration of B. longum 35624 to mice of the T cell transfer colitis model prevented disease symptoms, whereas sEPSneg did not protect against the development of colitis, with associated enhanced recruitment of IL-17+ lymphocytes to the gut. Moreover, intranasal administration of sEPSneg also resulted in enhanced recruitment of IL-17+ lymphocytes to the murine lung. These data demonstrate that the particular exopolysaccharide produced by B. longum 35624 plays an essential role in dampening proinflammatory host responses to the strain and that loss of exopolysaccharide production results in the induction of local TH17 responses. IMPORTANCE: Particular gut commensals, such as B. longum 35624, are known to contribute positively to the development of mucosal immune cells, resulting in protection from inflammatory diseases. However, the molecular basis and mechanisms for these commensal-host interactions are poorly described. In this report, an exopolysaccharide was shown to be decisive in influencing the immune response to the bacterium. We generated an isogenic mutant unable to produce exopolysaccharide and observed that this mutation caused a dramatic change in the response of human immune cells in vitro. In addition, the use of mouse models confirmed that lack of exopolysaccharide production induces inflammatory responses to the bacterium. These results implicate the surface-associated exopolysaccharide of the B. longum 35624 cell envelope in the prevention of aberrant inflammatory responses
Examining the Role of Narrative Performance Appraisal Comments on Performance
Despite their prevalence in performance appraisal systems and purported importance in theory, narrative performance appraisal comments have been rarely examined. This study aimed to contribute to the literature by developing and testing a theory of quality narrative feedback. The author argues that managerial feedback that is both directive (i.e., lengthy, specific, and includes goals) and motivational (i.e., positive and high in interactional justice) would be related to year-lagged performance. Negative and positive emotions are also proposed as mediators of this relationship. Performance appraisal comments were coded for a sample of 1,019 clinical nurses. The structural equations modeling results provided preliminary evidence that feedback favorability and interactional justice demonstrated significant direct and indirect (through positive and negative emotion) effects on year-lagged employee performance. © 2013 Copyright Taylor and Francis Group, LLC
Measurement of Angular Distributions and R= sigma_L/sigma_T in Diffractive Electroproduction of rho^0 Mesons
Production and decay angular distributions were extracted from measurements
of exclusive electroproduction of the rho^0(770) meson over a range in the
virtual photon negative four-momentum squared 0.5< Q^2 <4 GeV^2 and the
photon-nucleon invariant mass range 3.8< W <6.5 GeV. The experiment was
performed with the HERMES spectrometer, using a longitudinally polarized
positron beam and a ^3He gas target internal to the HERA e^{+-} storage ring.
The event sample combines rho^0 mesons produced incoherently off individual
nucleons and coherently off the nucleus as a whole. The distributions in one
production angle and two angles describing the rho^0 -> pi+ pi- decay yielded
measurements of eight elements of the spin-density matrix, including one that
had not been measured before. The results are consistent with the dominance of
helicity-conserving amplitudes and natural parity exchange. The improved
precision achieved at 47 GeV,
reveals evidence for an energy dependence in the ratio R of the longitudinal to
transverse cross sections at constant Q^2.Comment: 15 pages, 15 embedded figures, LaTeX for SVJour(epj) document class
Revision: Fig. 15 corrected, recent data added to Figs. 10,12,14,15; minor
changes to tex
Observation of a Coherence Length Effect in Exclusive Rho^0 Electroproduction
Exclusive incoherent electroproduction of the rho^0(770) meson from 1H, 2H,
3He, and 14N targets has been studied by the HERMES experiment at squared
four-momentum transfer Q**2>0.4 GeV**2 and positron energy loss nu from 9 to 20
GeV. The ratio of the 14N to 1H cross sections per nucleon, known as the
nuclear transparency, was found to decrease with increasing coherence length of
quark-antiquark fluctuations of the virtual photon. The data provide clear
evidence of the interaction of the quark- antiquark fluctuations with the
nuclear medium.Comment: RevTeX, 5 pages, 3 figure
Determination of the Deep Inelastic Contribution to the Generalised Gerasimov-Drell-Hearn Integral for the Proton and Neutron
The virtual photon absorption cross section differences [sigma_1/2-sigma_3/2]
for the proton and neutron have been determined from measurements of polarised
cross section asymmetries in deep inelastic scattering of 27.5 GeV
longitudinally polarised positrons from polarised 1H and 3He internal gas
targets. The data were collected in the region above the nucleon resonances in
the kinematic range nu < 23.5 GeV and 0.8 GeV**2 < Q**2 < 12 GeV**2. For the
proton the contribution to the generalised Gerasimov-Drell-Hearn integral was
found to be substantial and must be included for an accurate determination of
the full integral. Furthermore the data are consistent with a QCD
next-to-leading order fit based on previous deep inelastic scattering data.
Therefore higher twist effects do not appear significant.Comment: 6 pages, 3 figures, 1 table, revte
- …