Few-Shot Single-View 3-D Object Reconstruction with Compositional Priors

The impressive performance of deep convolutional neural networks in single-view 3D reconstruction suggests that these models perform non-trivial reasoning about the 3D structure of the output space. However, recent work has challenged this belief, showing that complex encoder-decoder architectures perform similarly to nearest-neighbor baselines or simple linear decoder models that exploit large amounts of per category data in standard benchmarks. On the other hand settings where 3D shape must be inferred for new categories with few examples are more natural and require models that generalize about shapes. In this work we demonstrate experimentally that naive baselines do not apply when the goal is to learn to reconstruct novel objects using very few examples, and that in a \emph{few-shot} learning setting, the network must learn concepts that can be applied to new categories, avoiding rote memorization. To address deficiencies in existing approaches to this problem, we propose three approaches that efficiently integrate a class prior into a 3D reconstruction model, allowing to account for intra-class variability and imposing an implicit compositional structure that the model should learn. Experiments on the popular ShapeNet database demonstrate that our method significantly outperform existing baselines on this task in the few-shot setting

Letters to the Editor Regarding NASW Press Censorship Issue

LETTERS TO THE EDITOR REGARDING NASW PRESS CENSORSHIP Marcia B. Cohen, Co-editor, Journal of Progressive Human Services Richard Hoefer, Editor, Journal of Policy Practice Tony Tripodi, Former Editor of Social Work Research Former Co-editor of Journal of Social Work Research and Evaluation Stanley L. Witkin, Former Editor-in-Chief, Social Work Elizabeth J. Clark, Executive Director, National Association of Social Workers (NASW

A progressive refinement approach for the visualisation of implicit surfaces

Visualising implicit surfaces with the ray casting method is a slow procedure. The design cycle of a new implicit surface is, therefore, fraught with long latency times as a user must wait for the surface to be rendered before being able to decide what changes should be introduced in the next iteration. In this paper, we present an attempt at reducing the design cycle of an implicit surface modeler by introducing a progressive refinement rendering approach to the visualisation of implicit surfaces. This progressive refinement renderer provides a quick previewing facility. It first displays a low quality estimate of what the final rendering is going to be and, as the computation progresses, increases the quality of this estimate at a steady rate. The progressive refinement algorithm is based on the adaptive subdivision of the viewing frustrum into smaller cells. An estimate for the variation of the implicit function inside each cell is obtained with an affine arithmetic range estimation technique. Overall, we show that our progressive refinement approach not only provides the user with visual feedback as the rendering advances but is also capable of completing the image faster than a conventional implicit surface rendering algorithm based on ray casting

Luteinizing Hormone-Releasing Hormone in the Vomeronasal System and Terminal Nerve of the Hamster a

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74742/1/j.1749-6632.1987.tb36300.x.pd

Innovator resilience potential: A process perspective of individual resilience as influenced by innovation project termination

Innovation projects fail at an astonishing rate. Yet, the negative effects of innovation project failures on the team members of these projects have been largely neglected in research streams that deal with innovation project failures. After such setbacks, it is vital to maintain or even strengthen project members’ innovative capabilities for subsequent innovation projects. For this, the concept of resilience, i.e. project members’ potential to positively adjust (or even grow) after a setback such as an innovation project failure, is fundamental. We develop the second-order construct of innovator resilience potential, which consists of six components – self-efficacy, outcome expectancy, optimism, hope, self-esteem, and risk propensity – that are important for project members’ potential of innovative functioning in innovation projects subsequent to a failure. We illustrate our theoretical findings by means of a qualitative study of a terminated large-scale innovation project, and derive implications for research and management

Activation in a Frontoparietal Cortical Network Underlies Individual Differences in the Performance of an Embedded Figures Task

The Embedded Figures Test (EFT) requires observers to search for a simple geometric shape hidden inside a more complex figure. Surprisingly, performance in the EFT is negatively correlated with susceptibility to illusions of spatial orientation, such as the Roelofs effect. Using fMRI, we previously demonstrated that regions in parietal cortex are involved in the contextual processing associated with the Roelofs task. In the present study, we found that similar parietal regions (superior parietal cortex and precuneus) were more active during the EFT than during a simple matching task. Importantly, these parietal activations overlapped with regions found to be involved during contextual processing in the Roelofs illusion. Additional parietal and frontal areas, in the right hemisphere, showed strong correlations between brain activity and behavioral performance during the search task. We propose that the posterior parietal regions are necessary for processing contextual information across many different, but related visuospatial tasks, with additional parietal and frontal regions serving to coordinate this processing in participants proficient in the task

Zika virus infection in pregnancy and adverse fetal outcomes in São Paulo State, Brazil: a prospective cohort study.

Robust epidemiological and biological evidence supports a causal link between prenatal Zika Virus (ZIKV) infection and congenital brain abnormalities including microcephaly. However, it remains uncertain if ZIKV infection in pregnancy also increases the risk for other adverse fetal and birth outcomes. In a prospective cohort study we investigated the influence of ZIKV on the prevalence of prematurity, low birth weight, small-for-gestational-age, and fetal death as well as microcephaly (i.e., overall and disproportionate) in the offspring of women attending a high-risk pregnancy clinic during the recent ZIKV outbreak in Brazil. During the recruitment period (01 March 2016-23 August 2017), urine samples were tested for ZIKV by RT-PCR from all women attending the high-risk pregnancy clinic at Jundiaí University Hospital and from the neonates after delivery. Of the 574 women evaluated, 44 (7.7%) were ZIKV RT-PCR positive during pregnancy. Of the 409 neonates tested, 19 (4.6%) were ZIKV RT-PCR positive in the first 10 days of life. In this cohort, maternal ZIKV exposure was not associated with increased risks of prematurity, low birth weight, small-for-gestational-age, or fetal death. However, relative to ZIKV-negative neonates, ZIKV-positive infants had a five-fold increased risk of microcephaly overall (RR 5.1, 95% CI 1.2-22.5) and a ten-fold increased risk of disproportionate microcephaly (RR 10.3, 95% CI 2.0-52.6). Our findings provide new evidence that, in a high-risk pregnancy cohort, ZIKV RT-PCR positivity in the neonate at birth is strongly associated with microcephaly. However, ZIKV infection during pregnancy does not appear to influence the risks of prematurity, low birth weight, small-for-gestational-age or fetal death in women who already have gestational comorbidities. The results suggest disproportion between neonatal head circumference and weight may be a useful screening indicator for the detection of congenital microcephaly associated with ZIKV infection