Urban Radiance Field Representation with Deformable Neural Mesh Primitives

Neural Radiance Fields (NeRFs) have achieved great success in the past few years. However, most current methods still require intensive resources due to ray marching-based rendering. To construct urban-level radiance fields efficiently, we design Deformable Neural Mesh Primitive~(DNMP), and propose to parameterize the entire scene with such primitives. The DNMP is a flexible and compact neural variant of classic mesh representation, which enjoys both the efficiency of rasterization-based rendering and the powerful neural representation capability for photo-realistic image synthesis. Specifically, a DNMP consists of a set of connected deformable mesh vertices with paired vertex features to parameterize the geometry and radiance information of a local area. To constrain the degree of freedom for optimization and lower the storage budgets, we enforce the shape of each primitive to be decoded from a relatively low-dimensional latent space. The rendering colors are decoded from the vertex features (interpolated with rasterization) by a view-dependent MLP. The DNMP provides a new paradigm for urban-level scene representation with appealing properties: $(1)$ High-quality rendering. Our method achieves leading performance for novel view synthesis in urban scenarios. $(2)$ Low computational costs. Our representation enables fast rendering (2.07ms/1k pixels) and low peak memory usage (110MB/1k pixels). We also present a lightweight version that can run 33$\times$ faster than vanilla NeRFs, and comparable to the highly-optimized Instant-NGP (0.61 vs 0.71ms/1k pixels). Project page: \href{https://dnmp.github.io/}{https://dnmp.github.io/}.Comment: Accepted to ICCV202

Deep Variational Luenberger-type Observer for Stochastic Video Prediction

Considering the inherent stochasticity and uncertainty, predicting future video frames is exceptionally challenging. In this work, we study the problem of video prediction by combining interpretability of stochastic state space models and representation learning of deep neural networks. Our model builds upon an variational encoder which transforms the input video into a latent feature space and a Luenberger-type observer which captures the dynamic evolution of the latent features. This enables the decomposition of videos into static features and dynamics in an unsupervised manner. By deriving the stability theory of the nonlinear Luenberger-type observer, the hidden states in the feature space become insensitive with respect to the initial values, which improves the robustness of the overall model. Furthermore, the variational lower bound on the data log-likelihood can be derived to obtain the tractable posterior prediction distribution based on the variational principle. Finally, the experiments such as the Bouncing Balls dataset and the Pendulum dataset are provided to demonstrate the proposed model outperforms concurrent works

Aqua­trinitrato[2,4,6-tris­(pyridin-2-yl)-1,3,5-triazine]neodymium(III) dihydrate

In the title compound, [Nd(NO3)3(C18H12N6)(H2O)]·2H2O, the Nd3+ ion is in a distorted bicapped square-anti­prismatic geometry formed by three N atoms from the 2,4,6-tris­(pyridin-2-yl)-1,3,5-triazine (TPTZ) ligand, six O atoms from the three nitrate anions and one O atom from the aqua ligand. The mol­ecules are linked by O—H⋯O and O—H⋯N hydrogen bonds. Two types of π–π stacking inter­actions occur between the TPTZ ligands of adjacent complexes [centroid-to-centroid distances = 3.760 (4) and 3.870 (3) Å]

Cold quark matter in a quasiparticle model: thermodynamic consistency and stellar properties

The strong coupling in the effective quark mass was usually taken as a constant in a quasiparticle model while it is, in fact, running with an energy scale. With a running coupling, however, the thermodynamic inconsistency problem appears in the conventional treatment. We show that the renormalization subtraction point should be taken as a function of the summation of the biquadratic chemical potentials if the quark's current masses vanish, in order to ensure full thermodynamic consistency. Taking the simplest form, we study the properties of up-down ($ud$) quark matter, and confirm that the revised quasiparticle model fulfills the quantitative criteria for thermodynamic consistency. Moreover, we find that the maximum mass of an $ud$ quark star can be larger than two times the solar mass, reaching up to $2.31M_{\odot}$, for reasonable model parameters. However, to further satisfy the upper limit of tidal deformability $\tilde{\Lambda}_{1.4}\leq 580$ observed in the event GW170817, the maximum mass of an $ud$ quark star can only be as large as $2.08M_{\odot}$, namely $M_{\text{max}}\lesssim2.08M_{\odot}$. In other words, our results indicate that the measured tidal deformability for event GW170817 places an upper bound on the maximum mass of $ud$ quark stars, but which does not rule out the possibility of the existence of quark stars composed of $ud$ quark matter, with a mass of about two times the solar mass.Comment: 10 pages, 8 figure

Examining geodetic glacier mass balance in the eastern Pamir transition zone

This research was supported by the Key Research Program of Frontier Sciences CAS [QYZDY-SSW-DQC026] and the National Natural Science Foundation of China [41590853]. SRTM DEM and NASA HMA DEM data were sourced from NASA Earthdata (https://earthdata.nasa.gov/), and the ALOS Global Digital Surface Model (AW3D30) was sourced from JAXA (https://www.eorc.jaxa.jp/ALOS/en/aw3d30/index.htm). ALOS PRISM level-1B1 products were ordered from http://en.alos-pasco.com/alos/prism/ under a 4th ALOS RA data grant awarded to Quincey (PI No. 1008). Landsat-7 and Landsat-8 images can be freely downloaded from http://glovis.usgs.gov. Randolph Glacier Inventory data were acquired from Global Land Ice Measurements from Space (GLIMS) (RGI Consortium, 2017). Lv acknowledges program B for outstanding PhD candidates of Nanjing University and the support from the Chinese Scholarship Council (CSC) for studying at the University of Leeds.Glaciers in the eastern Pamir have reportedly been gaining mass during recent decades, even though glaciers in most other regions in High Mountain Asia have been in recession. Questions still remain about whether the trend is strengthening or weakening, and how far the positive balances extend into the eastern Pamir. To address these gaps, we use three different digital elevation models to reconstruct glacier surface elevation changes over two periods (2000–09 and 2000–15/16). We characterize the eastern Pamir as a zone of transition from positive to negative mass balance with the boundary lying at the northern end of Kongur Tagh, and find that glaciers situated at higher elevations are those with the most positive balances. Most (67% of 55) glaciers displayed a net mass gain since the 21st century. This led to an increasing regional geodetic glacier mass balance from −0.06 ± 0.16 m w.e. a−1 in 2000–09 to 0.06 ± 0.04 m w.e. a−1 in 2000–15/16. Surge-type glaciers, which are prevalent in the eastern Pamir, showed fluctuations in mass balance on an individual scale during and after surges, but no statistical difference compared to non-surge-type glaciers when aggregated across the region.Publisher PDFPeer reviewe