Sin3DM: Learning a Diffusion Model from a Single 3D Textured Shape

Synthesizing novel 3D models that resemble the input example has long been pursued by researchers and artists in computer graphics. In this paper, we present Sin3DM, a diffusion model that learns the internal patch distribution from a single 3D textured shape and generates high-quality variations with fine geometry and texture details. Training a diffusion model directly in 3D would induce large memory and computational cost. Therefore, we first compress the input into a lower-dimensional latent space and then train a diffusion model on it. Specifically, we encode the input 3D textured shape into triplane feature maps that represent the signed distance and texture fields of the input. The denoising network of our diffusion model has a limited receptive field to avoid overfitting, and uses triplane-aware 2D convolution blocks to improve the result quality. Aside from randomly generating new samples, our model also facilitates applications such as retargeting, outpainting and local editing. Through extensive qualitative and quantitative evaluation, we show that our model can generate 3D shapes of various types with better quality than prior methods.Comment: Project page: https://Sin3DM.github.io, Code: https://github.com/Sin3DM/Sin3D

Elements content in tree rings from Xi'an, China and environmental variations in the past 30 years

Using inductively coupled plasma mass spectrometry (ICP-MS) and inductively coupled plasma atomic emission spectroscopy (ICP-AES), the characteristics of chemical elements were analyzed in white poplar (Populus bonatii Levl.) and ailanthus (Ailanthus altissima (Mill.) Swingle) from three sites in the town of Xi'an, China. The results indicated that the concentration variations of Pb and Cd in tree rings were consistent with that of the environment where the trees were growing. P and Zn were translocated within tree rings to a certain degree, which led to an inaccurate pollution reconstruction. We also found that white poplar had a stronger absorptive capacity of Cd and Zn than ailanthus, which could make white poplar better as a species in environmental remediation. From this research we can see the great potential of tree rings for studying the history of different element pollution in the environment, showing that dendrochemical methods could be used as a powerful component in environmental monitoring programmes, to reconstruct past pollution history at the time when monitoring systems were not yet installed. (c) 2017 Elsevier B.V. All rights reserved

Tree-ring-based precipitation reconstruction in the source region of Weihe River, northwest China since AD 1810

A tree-ring width chronology of Picea purpurea Mast from Mt. Shouyang in the source region of Weihe River (SWR), northwest China, was developed in this study. Correlation analysis showed that the precipitation from previous August to current July was the limiting climate factor of tree growth. Using a reliable and stable linear regression model, which explained 42.6% of the variance of the actual precipitation during the calibration period from 1958 to 2014, a 205-year long precipitation series was reconstructed for the SWR. The dry years in the reconstruction were well supported by historical documents, and famous historical droughts were also recorded in the dry periods of a low-frequency scale of the reconstructed precipitation. As demonstrated by the spatial correlation patterns, the reconstructed series compared well with other hydroclimate records for northwest China, indicating that it could represent large-scale hydroclimate changes. The 2-8-year interannual cycles and the interdecadal quasiperiods of 15.9 years and 18.6 years revealed that the precipitation in this region was probably affected by the El Nino-Southern Oscillation and North Atlantic Oscillation. The dry/wet years corresponded well with the El Nino/La Nina events and the SWR commonly experienced droughts during the low periods of North Atlantic Oscillation