Pix3D: Dataset and Methods for Single-Image 3D Shape Modeling

We study 3D shape modeling from a single image and make contributions to it in three aspects. First, we present Pix3D, a large-scale benchmark of diverse image-shape pairs with pixel-level 2D-3D alignment. Pix3D has wide applications in shape-related tasks including reconstruction, retrieval, viewpoint estimation, etc. Building such a large-scale dataset, however, is highly challenging; existing datasets either contain only synthetic data, or lack precise alignment between 2D images and 3D shapes, or only have a small number of images. Second, we calibrate the evaluation criteria for 3D shape reconstruction through behavioral studies, and use them to objectively and systematically benchmark cutting-edge reconstruction algorithms on Pix3D. Third, we design a novel model that simultaneously performs 3D reconstruction and pose estimation; our multi-task learning approach achieves state-of-the-art performance on both tasks.Comment: CVPR 2018. The first two authors contributed equally to this work. Project page: http://pix3d.csail.mit.ed

Pix3D: Dataset and Methods for Single-Image 3D Shape Modeling

We study 3D shape modeling from a single image and make contributions to it in three aspects. First, we present Pix3D, a large-scale benchmark of diverse image-shape pairs with pixel-level 2D-3D alignment. Pix3D has wide applications in shape-related tasks including reconstruction, retrieval, viewpoint estimation, etc. Building such a large-scale dataset, however, is highly challenging; existing datasets either contain only synthetic data, or lack precise alignment between 2D images and 3D shapes, or only have a small number of images. Second, we calibrate the evaluation criteria for 3D shape reconstruction through behavioral studies, and use them to objectively and systematically benchmark cutting-edge reconstruction algorithms on Pix3D. Third, we design a novel model that simultaneously performs 3D reconstruction and pose estimation; our multi-task learning approach achieves state-of-the-art performance on both tasks.Comment: CVPR 2018. The first two authors contributed equally to this work. Project page: http://pix3d.csail.mit.ed

Newly added characters and data matrix for oviraptorids phylogeny

This character description was modified from Longrich et al. (Longrich, N. R., Currie, P. J. & Dong, Z. M. 2010 A new oviraptorid (Dinosauria: Theropoda) from the Upper Cretaceous of Bayan Mandahu, Inner Mongolia. Palaeontology, 53, 945–960). The matrix was expanded by adding four characters and two taxa (Banji long and Ganzhousaurus nankangensis; for a total of 185 characters and 19 taxa)

Data from: A new oviraptorid (Dinosauria: Theropoda) from the Upper Cretaceous of southern China

This paper describes a new oviraptorid dinosaur taxon, Ganzhousaurus nankangensis gen. et sp. nov., based on a specimen collected from the Upper Cretaceous Nanxiong Formation of Nankang County, Ganzhou City, Jiangxi Province, southern China. This new taxon is distinguishable from other oviraptorids based on the following unique combination of primitive and derived features: relatively shallow dentary; absence of fossa or pneumatopore on lateral surface of dentary; weakly downturned anterior mandibular end; shallow depression immediately surrounding anterior margin of external mandibular fenestra; external mandibular fenestra subdivided by anterior process of surangular; dentary posteroventral process slight-ly twisted and positioned on mandibular ventrolateral surface; shallow longitudinal groove along medial surface of den-tary posteroventral process; angular anterior process wider transversely than deep dorsoventrally; sharp groove along ventrolateral surface of angular anterior process; ventral border of external mandibular fenestra formed mainly by angular; ventral flange along distal half of metatarsal II; and arctometatarsal condition absent. Phylogenetic analysis places Ganzhousaurus nankangensis gen. et sp. nov. in the clade Oviraptoridae, together with Oviraptor, Citipati, Rinchenia and the unnamed Zamyn Khondt oviraptorid

Distribution, Sources, and Risk Assessment of Organochlorine Pesticides in Water from Beiluo River, Loess Plateau, China

The Loess Plateau has been a focus of public discussion and environmental concerns over the past three decades. In this study, in order to investigate the effect of OCP pollution in water of the Beiluo River, concentrations of 25 OCPs at 17 locations in the water were examined. The results showed that the concentration of ∑OCPs in the water ranged from 1.76 to 32.57 ng L−1, with an average concentration of 7.23 ng L−1. Compared with other basins in China and abroad, the OCP content in the Beiluo River was at a medium level. Hexachlorocyclohexane (HCH) pollution in the Beiluo River was mainly from the mixed input of lindane and technical HCHs. Dichlorodiphenyltrichloroethane (DDT) pollution was mainly from the mixed input of technical DDTs and dicofol. Most of the OCP pollution came from historical residues. The risk assessment results showed that hexachlorobenzene (HCB) and endosulfan had high ecological risks in the middle and lower reaches of the Beiluo River. Most residual OCPs were not sufficient to pose carcinogenic and non-carcinogenic health risks to humans. The results of this study can provide a reference for OCP prevention and control and watershed environmental management

A Novel Methodology for Predicting the Production of Horizontal CSS Wells in Offshore Heavy Oil Reservoirs Using Particle Swarm Optimized Neural Network

Cyclic steam stimulation (CSS) is one of the main offshore heavy oil recovery methods used. Predicting the production of horizontal CSS wells is significant for developing offshore heavy oil reservoirs. Currently, the existing reservoir numerical simulation and analytical models are the two major methods to predict the production of horizontal CSS wells. The reservoir numerical simulation method is tedious and time-consuming, while the analytical models need many assumptions, decreasing models’ accuracy. Therefore, in this study, a novel methodology combining the particle swarm optimization algorithm (PA) and long short-term memory (LM) model was developed to predict the production of horizontal CSS wells. First, a simulation model was established to calculate the cumulative oil production (COP) of horizontal CSS wells under different well, geological, and operational parameters, and then the correlations between the calculated COP and parameters were analyzed by Pearson correlation coefficient to select the input variables and to generate the initial data set. Then, a PA-LM model for the COP of horizontal CSS wells was developed by utilizing the PA to determine the optimal hyperparameters of the LM model. Finally, the accuracy of the PA-LM model was validated by the initial data set and actual production data. The results showed that, compared with the LM model, the mean absolute percentage error (MAPE) of the testing set for the PA-LM model decreased by 4.27%, and the percentage of the paired points in zone A increased by 2.8% in the Clarke error grids. In addition, the MAPEs of the training set for the PA-LM and LM models stabilized at 267 and 304 epochs, respectively. Therefore, the proposed PA-LM model had a higher accuracy, a stronger generalization ability, and a faster convergence rate. The MAPEs of the actual and predicted COP of the wells B1H and B5H by the optimized PA-LM model were 8.66% and 5.93%, respectively, satisfying the requirements in field applications

Coupled ESR and U-series dating of fossil teeth from Yiyuan hominin site, northern China

Coupled ESR and U-series analyses of mammalian fossil teeth were carried out on two localities of Yiyuan hominin site (Locality 1 and 3) in northern China. The U-migration history of the fossil samples could be reconstructed by the combination of the two techniques, and overcome the limitation of stand-alone ESR and U-series age estimation. We obtained a combined ESR/U-series age (AU model) range from ~420 to 320 ka from nine teeth recovered from the two localities, which pinpoints the deposition of hominin layer of Yiyuan site to MIS 11 to 9. The age results in this study places Yiyuan site at the same time range of Zhoukoudian Locality 1 and Hexian Homo erectus sites. Comparing with other hominin sites, this study of Yiyuan Homo erectus site highlights the possibility of coexistence between Homo erectus and archaic H. sapiens in China