Aleth-NeRF: Low-light Condition View Synthesis with Concealing Fields

Common capture low-light scenes are challenging for most computer vision techniques, including Neural Radiance Fields (NeRF). Vanilla NeRF is viewer-centred that simplifies the rendering process only as light emission from 3D locations in the viewing direction, thus failing to model the low-illumination induced darkness. Inspired by emission theory of ancient Greek that visual perception is accomplished by rays casting from eyes, we make slight modifications on vanilla NeRF to train on multiple views of low-light scene, we can thus render out the well-lit scene in an unsupervised manner. We introduce a surrogate concept, Concealing Fields, that reduce the transport of light during the volume rendering stage. Specifically, our proposed method, Aleth-NeRF, directly learns from the dark image to understand volumetric object representation and concealing field under priors. By simply eliminating Concealing Fields, we can render a single or multi-view well-lit image(s) and gain superior performance over other 2D low light enhancement methods. Additionally, we collect the first paired LOw-light and normal-light Multi-view (LOM) datasets for future research.Comment: website page: https://cuiziteng.github.io/Aleth_NeRF_web

Evolution of Winning Solutions in the 2021 Low-Power Computer Vision Challenge

Mobile and embedded devices are becoming ubiquitous. Applications such as rescue with autonomous robots and event analysis on traffic cameras rely on devices with limited power supply and computational sources. Thus, the demand for efficient computer vision algorithms increases. Since 2015, we have organized the IEEE Low-Power Computer Vision Challenge to advance the state of the art in low-power computer vision. We describe the competition organizing details including the challenge design, the reference solution, the dataset, the referee system, and the evolution of the solutions from two winning teams. We examine the winning teams’ development patterns and design decisions, focusing on their techniques to balance power consumption and accuracy. We conclude that a successful competition needs a well-designed reference solution and automated referee system, and a solution with modularized components is more likely to win. We hope this paper provides guidelines for future organizers and contestants of computer vision competitions

Quantitatively analyzing the failure processes of rechargeable Li metal batteries.

Practical use of lithium (Li) metal for high–energy density lithium metal batteries has been prevented by the continuous formation of Li dendrites, electrochemically isolated Li metal, and the irreversible formation of solid electrolyte interphases (SEIs). Differentiating and quantifying these inactive Li species are key to understand the failure mode. Here, using operando nuclear magnetic resonance (NMR) spectroscopy together with ex situ titration gas chromatography (TGC) and mass spectrometry titration (MST) techniques, we established a solid foundation for quantifying the evolution of dead Li metal and SEI separately. The existence of LiH is identified, which causes deviation in the quantification results of dead Li metal obtained by these three techniques. The formation of inactive Li under various operating conditions has been studied quantitatively, which revealed a general “two-stage” failure process for the Li metal. The combined techniques presented here establish a benchmark to unravel the complex failure mechanism of Li metal

Exosomes and exosome composite scaffolds in periodontal tissue engineering

Promoting complete periodontal regeneration of damaged periodontal tissues, including dental cementum, periodontal ligament, and alveolar bone, is one of the challenges in the treatment of periodontitis. Therefore, it is urgent to explore new treatment strategies for periodontitis. Exosomes generated from stem cells are now a promising alternative to stem cell therapy, with therapeutic results comparable to those of their blast cells. It has great potential in regulating immune function, inflammation, microbiota, and tissue regeneration and has shown good effects in periodontal tissue regeneration. In addition, periodontal tissue engineering combines exosomes with biomaterial scaffolds to maximize the therapeutic advantages of exosomes. Therefore, this article reviews the progress, challenges, and prospects of exosome and exosome-loaded composite scaffolds in periodontal regeneration

A study on crown interception with four dominant tree species : A direct measurement

An experiment was conducted to concentrate on the rainfall interception process of individual trees for four common species in Beijing, China, which included needle species (Platycladus orientalis and Pinus tabulaeformis) and broadleaf species (Quercus variabilis and Acer truncatum). Two types of interception storages, the maximum (Cmax) and the minimum interception storage (Cmin), were examined at four simulated rainfall intensities (from 11.7 to 78.5 mm hr-1). Results showed that an average of 91% of Cmax for all the species was intercepted during the first 10 minutes of rainfall, while 45% of Cmax drained off after rainfall cessation. Leaf area index (LAI) and leaf area (LA) were significantly correlated (p < 0.05) with Cmax and Cmin, while such significant correlations were not found between rainfall intensity and Cmax and Cmin. Average Cmax and Cmin across all the species corresponded to 3 and 1% of gross rainfall. Mean Cmax and Cmin of the needle species were 3.0 and 1.8 times larger than that for the broadleaf ones. Results revealed that interception was a dynamic process which encompassed three phases. In addition, LAI and LA were valid predictors of interception in small trees, and deserve further test in forest stands

Convergence and divergence emerging in climatic controls of polynomial trends for northern ecosystem productivity over 2000–2018

Southwest China has been the largest terrestrial carbon sink in China over the past 30 years, but has recently experienced a succession of droughts caused by high precipitation variability, potentially threatening vegetation productivity in the region. Yet, the impact of precipitation anomalies on the vegetation primary productivity is poorly known. We used an asymmetry index (AI) to explore possible asymmetric productivity responses to precipitation anomalies in Southwest China from 2003 to 2018, using a precipitation dataset, combined with gross primary productivity (GPP), net primary productivity (NPP), and vegetation optical depth (VOD) products. Our results indicate that the vegetation primary productivity of Southwest China shows a negative asymmetry, suggesting that the increase of vegetation primary productivity during wet years exceeds the decrease during dry years. However, this negative asymmetry of vegetation primary productivity was shifted towards a positive asymmetry during the period of analysis, suggesting that the resistance of vegetation to drought, has increased with the rise in the occurrence of drought events. Among the different biomes, grassland vegetation primary productivity had the highest sensitivity to precipitation anomalies, indicating that grasslands are more flexible than other biomes and able to adjust primary productivity in response to precipitation anomalies. Furthermore, our results showed that the asymmetry of vegetation primary productivity was influenced by the effects of temperature, precipitation, solar radiation, and anthropogenic and topographic factors. These findings improve our understanding of the response of vegetation primary productivity to climate change over Southwest China