PS-FCN: A Flexible Learning Framework for Photometric Stereo

This paper addresses the problem of photometric stereo for non-Lambertian surfaces. Existing approaches often adopt simplified reflectance models to make the problem more tractable, but this greatly hinders their applications on real-world objects. In this paper, we propose a deep fully convolutional network, called PS-FCN, that takes an arbitrary number of images of a static object captured under different light directions with a fixed camera as input, and predicts a normal map of the object in a fast feed-forward pass. Unlike the recently proposed learning based method, PS-FCN does not require a pre-defined set of light directions during training and testing, and can handle multiple images and light directions in an order-agnostic manner. Although we train PS-FCN on synthetic data, it can generalize well on real datasets. We further show that PS-FCN can be easily extended to handle the problem of uncalibrated photometric stereo.Extensive experiments on public real datasets show that PS-FCN outperforms existing approaches in calibrated photometric stereo, and promising results are achieved in uncalibrated scenario, clearly demonstrating its effectiveness.Comment: ECCV 2018: https://guanyingc.github.io/PS-FC

A Model of Curvature-Induced Phase Transitions in Inflationary Universe

Chiral phase transitions driven by space-time curvature effects are investigated in de Sitter space in the supersymmetric Nambu-Jona-Lasinio model with soft supersymmetry breaking. The model is considered to be suitable for the analysis of possible phase transitions in inflationary universe. It is found that a restoration of the broken chiral symmetry takes place in two patterns for increasing curvature : the first order and second order phase transition respectively depending on initial settings of the four-body interaction parameter and the soft supersymmetry breaking parameter. The critical curves expressing the phase boundaries in these parameters are obtained. Cosmological implications of the result are discussed in connection with bubble formations and the creation of cosmic strings during the inflationary era.Comment: 12 pages, 3 figures, REVTe

Curvature-induced phase transitions in the inflationary universe - Supersymmetric Nambu-Jona-Lasinio Model in de Sitter spacetime -

The phase structure associated with the chiral symmetry is thoroughly investigated in de Sitter spacetime in the supersymmetric Nambu-Jona-Lasinio model with supersymmetry breaking terms. The argument is given in the three and four space-time dimensions in the leading order of the 1/N expansion and it is shown that the phase characteristics of the chiral symmetry is determined by the curvature of de Sitter spacetime. It is found that the symmetry breaking takes place as the first order as well as second order phase transition depending on the choice of the coupling constant and the parameter associated with the supersymmetry breaking term. The critical curves expressing the phase boundary are obtained. We also discuss the model in the context of the chaotic inflation scenario where topological defects (cosmic strings) develop during the inflation.Comment: 29 pages, 6 figures, REVTe

Reassortment and Mutations Associated with Emergence and Spread of Oseltamivir-Resistant Seasonal Influenza A/H1N1 Viruses in 2005–2009

A dramatic increase in the frequency of the H275Y mutation in the neuraminidase (NA), conferring resistance to oseltamivir, has been detected in human seasonal influenza A/H1N1 viruses since the influenza season of 2007–2008. The resistant viruses emerged in the ratio of 14.3% and quickly reached 100% in Taiwan from September to December 2008. To explore the mechanisms responsible for emergence and spread of the resistant viruses, we analyzed the complete genome sequences of 25 viruses collected during 2005–2009 in Taiwan, which were chosen from various clade viruses, 1, 2A, 2B-1, 2B-2, 2C-1 and 2C-2 by the classification of hemagglutinin (HA) sequences. Our data revealed that the dominant variant, clade 2B-1, in the 2007–2008 influenza emerged through an intra-subtype 4+4 reassortment between clade 1 and 2 viruses. The dominant variant acquired additional substitutions, including A206T in HA, H275Y and D354G in NA, L30R and H41P in PB1-F2, and V411I and P453S in basic polymerase 2 (PB2) proteins and subsequently caused the 2008–2009 influenza epidemic in Taiwan, accompanying the widespread oseltamivir-resistant viruses. We also characterized another 3+5 reassortant virus which became double resistant to oseltamivir and amantadine. Comparison of oseltamivir-resistant influenza A/H1N1 viruses belonging to various clades in our study highlighted that both reassortment and mutations were associated with emergence and spread of these viruses and the specific mutation, H275Y, conferring to antiviral resistance, was acquired in a hitch-hiking mechanism during the viral evolutionary processes

PS-FCN: a flexible learning framework for photometric stereo

This paper addresses the problem of photometric stereo for non-Lambertian surfaces. Existing approaches often adopt simplified reflectance models to make the problem more tractable, but this greatly hinders their applications on real-world objects. In this paper, we propose a deep fully convolutional network, called PS-FCN, that takes an arbitrary number of images of a static object captured under different light directions with a fixed camera as input, and predicts a normal map of the object in a fast feed-forward pass. Unlike the recently proposed learning based method, PS-FCN does not require a pre-defined set of light directions during training and testing, and can handle multiple images and light directions in an order-agnostic manner. Although we train PS-FCN on synthetic data, it can generalize well on real datasets. We further show that PS-FCN can be easily extended to handle the problem of uncalibrated photometric stereo. Extensive experiments on public real datasets show that PS-FCN outperforms existing approaches in calibrated photometric stereo, and promising results are achieved in uncalibrated scenario, clearly demonstrating its effectiveness