OV-NeRF: Open-vocabulary Neural Radiance Fields with Vision and Language Foundation Models for 3D Semantic Understanding

The development of Neural Radiance Fields (NeRFs) has provided a potent representation for encapsulating the geometric and appearance characteristics of 3D scenes. Enhancing the capabilities of NeRFs in open-vocabulary 3D semantic perception tasks has been a recent focus. However, current methods that extract semantics directly from Contrastive Language-Image Pretraining (CLIP) for semantic field learning encounter difficulties due to noisy and view-inconsistent semantics provided by CLIP. To tackle these limitations, we propose OV-NeRF, which exploits the potential of pre-trained vision and language foundation models to enhance semantic field learning through proposed single-view and cross-view strategies. First, from the single-view perspective, we introduce Region Semantic Ranking (RSR) regularization by leveraging 2D mask proposals derived from SAM to rectify the noisy semantics of each training view, facilitating accurate semantic field learning. Second, from the cross-view perspective, we propose a Cross-view Self-enhancement (CSE) strategy to address the challenge raised by view-inconsistent semantics. Rather than invariably utilizing the 2D inconsistent semantics from CLIP, CSE leverages the 3D consistent semantics generated from the well-trained semantic field itself for semantic field training, aiming to reduce ambiguity and enhance overall semantic consistency across different views. Extensive experiments validate our OV-NeRF outperforms current state-of-the-art methods, achieving a significant improvement of 20.31% and 18.42% in mIoU metric on Replica and Scannet, respectively. Furthermore, our approach exhibits consistent superior results across various CLIP configurations, further verifying its robustness

Redistributing the Precision and Content in 3D-LUT-based Inverse Tone-mapping for HDR/WCG Display

ITM(inverse tone-mapping) converts SDR (standard dynamic range) footage to HDR/WCG (high dynamic range /wide color gamut) for media production. It happens not only when remastering legacy SDR footage in front-end content provider, but also adapting on-theair SDR service on user-end HDR display. The latter requires more efficiency, thus the pre-calculated LUT (look-up table) has become a popular solution. Yet, conventional fixed LUT lacks adaptability, so we learn from research community and combine it with AI. Meanwhile, higher-bit-depth HDR/WCG requires larger LUT than SDR, so we consult traditional ITM for an efficiency-performance trade-off: We use 3 smaller LUTs, each has a non-uniform packing (precision) respectively denser in dark, middle and bright luma range. In this case, their results will have less error only in their own range, so we use a contribution map to combine their best parts to final result. With the guidance of this map, the elements (content) of 3 LUTs will also be redistributed during training. We conduct ablation studies to verify method's effectiveness, and subjective and objective experiments to show its practicability. Code is available at: https://github.com/AndreGuo/ITMLUT.Comment: Accepted in CVMP2023 (the 20th ACM SIGGRAPH European Conference on Visual Media Production

Continued spread of HIV among injecting drug users in southern Sichuan Province, China

OBJECTIVE: To estimate HIV prevalence among injecting drug users (IDUs) in a drug trafficking city in southwest Sichuan Province, China. METHODS: A total of 314 IDUs was invited to participate in the cross-sectional survey in 2004 through community outreach recruitment and peer referrals. Blood sample was taken for HIV antibody testing and a structured questionnaire was administered to collect information on socio-demographics, drug using and sexual behaviors. RESULTS: HIV prevalence among IDUs was 17.8% (56/314), about one half higher than that in previous survey in 2002 (11.3%, 43/379). Yi and other minority ethnicity (Odds ratio [OR], 3.1; 95% confidence interval [CI], 1.7–5.8; P < 0.001), and total times of sharing injecting equipments 1–9 times versus none, OR, 2.7; 95% CI 1.2–6.2; P = 0.02; and ≥10 times versus none, OR, 7.5; 95% CI, 3.2–17.7; P < 0.001) were independent risk factors for HIV infection. CONCLUSION: IDUs with high prevalence rates of HIV and equipment sharing behavior in the drug trafficking city may serve a source for further spread of HIV to other areas in China. The increasing trend of HIV epidemic among IDUs underscores the urgency of scaling up interventions

QTL mapping and genomic selection of stem and branch diameter in soybean (Glycine max L.)

IntroductionSoybean stem diameter (SD) and branch diameter (BD) are closely related traits, and genetic clarification of SD and BD is crucial for soybean breeding.MethodsSD and BD were genetically analyzed by a population of 363 RIL derived from the cross between Zhongdou41 (ZD41) and ZYD02878 using restricted two-stage multi-locus genome-wide association, inclusive composite interval mapping, and three-variance component multi-locus random SNP effect mixed linear modeling. Then candidate genes of major QTLs were selected and genetic selection model of SD and BD were constructed respectively.Results and discussionThe results showed that SD and BD were significantly correlated (r = 0.74, P &lt; 0.001). A total of 93 and 84 unique quantitative trait loci (QTL) were detected for SD and BD, respectively by three different methods. There were two and ten major QTLs for SD and BD, respectively, with phenotypic variance explained (PVE) by more than 10%. Within these loci, seven genes involved in the regulation of phytohormones (IAA and GA) and cell proliferation and showing extensive expression of shoot apical meristematic genes were selected as candidate genes. Genomic selection (GS) analysis showed that the trait-associated markers identified in this study reached 0.47-0.73 in terms of prediction accuracy, which was enhanced by 6.56-23.69% compared with genome-wide markers. These results clarify the genetic basis of SD and BD, which laid solid foundation in regulation gene cloning, and GS models constructed could be potentially applied in future breeding programs

Genetic Diversity of Mycobacterium tuberculosis Isolates from Tibetans in Tibet, China

BACKGROUND: Tuberculosis (TB) is a serious health problem in Tibet where Tibetans are the major ethnic group. Although genotyping of Mycobacterium tuberculosis (M. tuberculosis) isolates is a valuable tool for TB control, our knowledge of population structure of M. tuberculosis circulating in Tibet is limited. METHODOLOGY/PRINCIPAL FINDINGS: In our study, a total of 576 M. tuberculosis isolates from Tibetans in Tibet, China, were analyzed via spoligotyping and 24-locus MIRU-VNTR. The Beijing genotype was the most prevalent family (90.63%, n = 522). Shared-type (ST) 1 was the most dominant genotype (88.89%, n = 512). We found that there was no association between the Beijing genotype and sex, age and treatment status. In this sample collection, 7 of the 24 MIRU-VNTR loci were highly or moderately discriminative according to their Hunter-Gaston discriminatory index. An informative set of 12 loci had similar discriminatory power with 24 loci set. CONCLUSIONS/SIGNIFICANCE: The population structure of M. tuberculosis isolates in Tibetans is homogeneous and dominated by Beijing genotype. The analysis of 24-locus MIRU-VNTR data might be useful to select appropriate VNTR loci for the genotyping of M. tuberculosis