Guided Deep Decoder: Unsupervised Image Pair Fusion

The fusion of input and guidance images that have a tradeoff in their information (e.g., hyperspectral and RGB image fusion or pansharpening) can be interpreted as one general problem. However, previous studies applied a task-specific handcrafted prior and did not address the problems with a unified approach. To address this limitation, in this study, we propose a guided deep decoder network as a general prior. The proposed network is composed of an encoder-decoder network that exploits multi-scale features of a guidance image and a deep decoder network that generates an output image. The two networks are connected by feature refinement units to embed the multi-scale features of the guidance image into the deep decoder network. The proposed network allows the network parameters to be optimized in an unsupervised way without training data. Our results show that the proposed network can achieve state-of-the-art performance in various image fusion problems.Comment: ECCV 202

Application guide for omics approaches to cell signaling

Research in signal transduction aims to identify the functions of different signaling pathways in physiological and pathological states. Traditional techniques using biochemical, genetic or cell biological approaches have made important contributions to our understanding of cellular signaling. However, the single-gene approach does not take into account the full complexity of cell signaling. With the availability of omics techniques, great progress has been made in understanding signaling networks. Omics approaches can be classified into two categories: 'molecular profiling', including genomic, proteomic, post-translational modification and interactome profiling; and 'molecular perturbation', including genetic and functional perturbations

Diacylglycerol triggers Rim101 pathway dependent necrosis in yeast: a model for lipotoxicity

The loss of lipid homeostasis can lead to lipid overload and is associated with a variety of disease states. However, little is known as to how the disruption of lipid regulation or lipid overload affects cell survival. In this study we investigated how excess diacylglycerol (DG), a cardinal metabolite suspected to mediate lipotoxicity, compromises the survival of yeast cells. We reveal that increased DG achieved by either genetic manipulation or pharmacological administration of 1,2-dioctanoyl-sn-glycerol (DOG) triggers necrotic cell death. The toxic effects of DG are linked to glucose metabolism and require a functional Rim101 signaling cascade involving the Rim21 dependent sensing complex and activation of a calpain-like protease. The Rim101 cascade is an established pathway that triggers a transcriptional response to alkaline or lipid stress. We propose that the Rim101 pathway senses DG-induced lipid perturbation and conducts a signaling response that either facilitates cellular adaptation or triggers lipotoxic cell death. Using established models of lipotoxicity i.e. high fat diet in Drosophila and palmitic acid administration in cultured human endothelial cells, we present evidence that the core mechanism underlying this calpain-dependent lipotoxic cell death pathway is phylogenetically conserved

A Survey on Time-of-Flight Stereo Fusion

Abstract. Due to the demand for depth maps of higher quality than possible with a single depth imaging technique today, there has been an increasing interest in the combination of different depth sensors to produce a “super-camera ” that is more than the sum of the individual parts. In this survey paper, we give an overview over methods for the fusion of Time-of-Flight (ToF) and passive stereo data as well as applications of the resulting high quality depth maps. Additionally, we provide a tutorial-based introduction to the principles behind ToF stereo fusion and the evaluation criteria used to benchmark these methods.

Building highly realistic facial modeling and animation: a survey

This paper provides a comprehensive survey on the techniques for human facial modeling and animation. The survey is carried out from two different perspectives: facial modeling, which concerns how to produce 3D face models, and facial animation, which regards how to synthesize dynamic facial expressions. To generate an individual face model, we can either perform individualization of a generic model or combine face models from an existing face collection. With respect to facial animation, we have further categorized the techniques into simulation-based, performance-driven and shape blend-based approaches. The strength and weakness of these techniques within each category are discussed, alongside with the applications of these techniques to various exploitations. In addition, a brief historical review of the technique evolution is provided. Limitations and future trend are discussed. Conclusions are drawn at the end of the paper