Directional Texture Editing for 3D Models

Texture editing is a crucial task in 3D modeling that allows users to automatically manipulate the surface materials of 3D models. However, the inherent complexity of 3D models and the ambiguous text description lead to the challenge in this task. To address this challenge, we propose ITEM3D, a \textbf{T}exture \textbf{E}diting \textbf{M}odel designed for automatic \textbf{3D} object editing according to the text \textbf{I}nstructions. Leveraging the diffusion models and the differentiable rendering, ITEM3D takes the rendered images as the bridge of text and 3D representation, and further optimizes the disentangled texture and environment map. Previous methods adopted the absolute editing direction namely score distillation sampling (SDS) as the optimization objective, which unfortunately results in the noisy appearance and text inconsistency. To solve the problem caused by the ambiguous text, we introduce a relative editing direction, an optimization objective defined by the noise difference between the source and target texts, to release the semantic ambiguity between the texts and images. Additionally, we gradually adjust the direction during optimization to further address the unexpected deviation in the texture domain. Qualitative and quantitative experiments show that our ITEM3D outperforms the state-of-the-art methods on various 3D objects. We also perform text-guided relighting to show explicit control over lighting. Our project page: https://shengqiliu1.github.io/ITEM3D.Comment: project page: https://shengqiliu1.github.io/ITEM3

Sparse Recovery for Bistatic MIMO Radar Imaging in the Presence of Array Gain Uncertainties

A sparse recovery based transmit-receive angle imaging scheme is proposed for bistatic multiple-input multiple-output (MIMO) radar. The redundancy of the transmit and receive angles in the same range cell is exploited to construct the sparse model. The imaging is then performed by compressive sensing method with consideration of both the transmit and receive array gain uncertainties. An additional constraint is imposed on the inverse of the transmit and receive array gain errors matrices to make the optimization problem of the CS solvable. The image of the targets can be reconstructed using small number of snapshots in the case of large array gain uncertainties. Simulation results confirm the effectiveness of the proposed scheme

Mapping forests in monsoon Asia with ALOS PALSAR 50-m mosaic images and MODIS imagery in 2010.

Extensive forest changes have occurred in monsoon Asia, substantially affecting climate, carbon cycle and biodiversity. Accurate forest cover maps at fine spatial resolutions are required to qualify and quantify these effects. In this study, an algorithm was developed to map forests in 2010, with the use of structure and biomass information from the Advanced Land Observation System (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) mosaic dataset and the phenological information from MODerate Resolution Imaging Spectroradiometer (MOD13Q1 and MOD09A1) products. Our forest map (PALSARMOD50 m F/NF) was assessed through randomly selected ground truth samples from high spatial resolution images and had an overall accuracy of 95%. Total area of forests in monsoon Asia in 2010 was estimated to be ~6.3 × 10(6 )km(2). The distribution of evergreen and deciduous forests agreed reasonably well with the median Normalized Difference Vegetation Index (NDVI) in winter. PALSARMOD50 m F/NF map showed good spatial and areal agreements with selected forest maps generated by the Japan Aerospace Exploration Agency (JAXA F/NF), European Space Agency (ESA F/NF), Boston University (MCD12Q1 F/NF), Food and Agricultural Organization (FAO FRA), and University of Maryland (Landsat forests), but relatively large differences and uncertainties in tropical forests and evergreen and deciduous forests

Identification of genes regulated by Wnt/β-catenin pathway and involved in apoptosis via microarray analysis

BACKGROUND: Wnt/β-catenin pathway has critical roles in development and oncogenesis. Although significant progress has been made in understanding the downstream signaling cascade of this pathway, little is known regarding Wnt/β-catenin pathway modification of the cellular apoptosis. METHODS: To identify potential genes regulated by Wnt/β-catenin pathway and involved in apoptosis, we used a stably integrated, inducible RNA interference (RNAi) vector to specific inhibit the expression and the transcriptional activity of β-catenin in HeLa cells. Meanwhile, we designed an oligonucleotide microarray covering 1384 apoptosis-related genes. Using oligonucleotide microarrays, a series of differential expression of genes was identified and further confirmed by RT-PCR. RESULTS: Stably integrated inducible RNAi vector could effectively suppress β-catenin expression and the transcriptional activity of β-catenin/TCF. Meanwhile, depletion of β-catenin in this manner made the cells more sensitive to apoptosis. 130 genes involved in some important cell-apoptotic pathways, such as PTEN-PI3K-AKT pathway, NF-κB pathway and p53 pathway, showed significant alteration in their expression level after the knockdown of β-catenin. CONCLUSION: Coupling RNAi knockdown with microarray and RT-PCR analyses proves to be a versatile strategy for identifying genes regulated by Wnt/β-catenin pathway and for a better understanding the role of this pathway in apoptosis. Some of the identified β-catenin/TCF directed or indirected target genes may represent excellent targets to limit tumor growth

RenderMe-360: A Large Digital Asset Library and Benchmarks Towards High-fidelity Head Avatars

Synthesizing high-fidelity head avatars is a central problem for computer vision and graphics. While head avatar synthesis algorithms have advanced rapidly, the best ones still face great obstacles in real-world scenarios. One of the vital causes is inadequate datasets -- 1) current public datasets can only support researchers to explore high-fidelity head avatars in one or two task directions; 2) these datasets usually contain digital head assets with limited data volume, and narrow distribution over different attributes. In this paper, we present RenderMe-360, a comprehensive 4D human head dataset to drive advance in head avatar research. It contains massive data assets, with 243+ million complete head frames, and over 800k video sequences from 500 different identities captured by synchronized multi-view cameras at 30 FPS. It is a large-scale digital library for head avatars with three key attributes: 1) High Fidelity: all subjects are captured by 60 synchronized, high-resolution 2K cameras in 360 degrees. 2) High Diversity: The collected subjects vary from different ages, eras, ethnicities, and cultures, providing abundant materials with distinctive styles in appearance and geometry. Moreover, each subject is asked to perform various motions, such as expressions and head rotations, which further extend the richness of assets. 3) Rich Annotations: we provide annotations with different granularities: cameras' parameters, matting, scan, 2D/3D facial landmarks, FLAME fitting, and text description. Based on the dataset, we build a comprehensive benchmark for head avatar research, with 16 state-of-the-art methods performed on five main tasks: novel view synthesis, novel expression synthesis, hair rendering, hair editing, and talking head generation. Our experiments uncover the strengths and weaknesses of current methods. RenderMe-360 opens the door for future exploration in head avatars.Comment: Technical Report; Project Page: 36; Github Link: https://github.com/RenderMe-360/RenderMe-36

Investigating behavior inhibition in obsessive‐compulsive disorder: Evidence from eye movements

We investigated the role of inhibition failure in Obsessive Compulsive Disorder (OCD) through an eye tracking experiment. Twenty‐five subjects with OCD were recruited, as well as 25 with Generalized Anxiety Disorder (GAD) and 25 healthy controls. A 3 (group: OCD group, GAD group and control group) × 2 (target eccentricity: far and near) × 2 (saccade task: prosaccade and antisaccade) mixed design was used, with all participants completing two sets of tasks involving both prosaccade (eye movement towards a target) and antisaccade (eye movement away from a target). The main outcome was the eye movement index, including the saccade latency (the time interval from the onset of the target screen to the first saccade) and the error rate of saccade direction. The antisaccade latency and antisaccade error rates for OCDs were much higher than those for GADs and healthy controls. OCDs had longer latency and error rates for antisaccades than for prosaccades, and for far‐eccentricity rather than near‐eccentricity stimuli. These results suggest that OCDs experience difficulty with behavior inhibition, and that they have higher visual sensitivity to peripheral stimuli. In particular, they show greatest difficulty in inhibiting behavior directed towards peripheral stimuli

The short-term associations of chronic obstructive pulmonary disease hospitalizations with meteorological factors and air pollutants in Southwest China: a time-series study

Chronic obstructive pulmonary disease (COPD) is the fourth major cause of mortality and morbidity worldwide and is projected to be the third by 2030. However, there is little evidence available on the associations of COPD hospitalizations with meteorological factors and air pollutants in developing countries/regions of Asia. In particular, no study has been done in western areas of China considering the nonlinear and lagged effects simultaneously. This study aims to evaluate the nonlinear and lagged associations of COPD hospitalizations with meteorological factors and air pollutants using time-series analysis. The modified associations by sex and age were also investigated. The distributed lag nonlinear model was used to establish the association of daily COPD hospitalizations of all 441 public hospitals in Chengdu, China from Jan/2015–Dec/2017 with the ambient meteorological factors and air pollutants. Model parameters were optimized based on quasi Akaike Information Criterion and model diagnostics was conducted by inspecting the deviance residuals. Subgroup analysis by sex and age was also performed. Temperature, relative humidity, wind and Carbon Monoxide (CO) have statistically significant and consistent associations with COPD hospitalizations. The cumulative relative risk (RR) was lowest at a temperature of 19℃ (relative humidity of 67%). Both extremely high and low temperature (and relative humidity) increase the cumulative RR. An increase of wind speed above 4 mph (an increase of CO above 1.44 mg/m3) significantly decreases (increases) the cumulative RR. Female populations were more sensitive to low temperature and high CO level; elderly (74+) populations are more sensitive to high relative humidity; younger populations (< = 74) are more susceptible to CO higher than 1.44 mg/m3. Therefore, people with COPD should avoid exposure to adverse environmental conditions of extreme temperatures and relative humidity, low wind speed and high CO level, especially for female and elderly patients who were more sensitive to extreme temperatures and relative humidity