73 research outputs found

    3D-TOGO: Towards Text-Guided Cross-Category 3D Object Generation

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    Text-guided 3D object generation aims to generate 3D objects described by user-defined captions, which paves a flexible way to visualize what we imagined. Although some works have been devoted to solving this challenging task, these works either utilize some explicit 3D representations (e.g., mesh), which lack texture and require post-processing for rendering photo-realistic views; or require individual time-consuming optimization for every single case. Here, we make the first attempt to achieve generic text-guided cross-category 3D object generation via a new 3D-TOGO model, which integrates a text-to-views generation module and a views-to-3D generation module. The text-to-views generation module is designed to generate different views of the target 3D object given an input caption. prior-guidance, caption-guidance and view contrastive learning are proposed for achieving better view-consistency and caption similarity. Meanwhile, a pixelNeRF model is adopted for the views-to-3D generation module to obtain the implicit 3D neural representation from the previously-generated views. Our 3D-TOGO model generates 3D objects in the form of the neural radiance field with good texture and requires no time-cost optimization for every single caption. Besides, 3D-TOGO can control the category, color and shape of generated 3D objects with the input caption. Extensive experiments on the largest 3D object dataset (i.e., ABO) are conducted to verify that 3D-TOGO can better generate high-quality 3D objects according to the input captions across 98 different categories, in terms of PSNR, SSIM, LPIPS and CLIP-score, compared with text-NeRF and Dreamfields

    Origin and evolution of the triploid cultivated banana genome

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    DATA AVAILABILITY : Genome assemblies of Cavendish, Gros Michel and Zebrina v2.0 have been deposited into NCBI under GenBank numbers JAVVNX000000000, JAVVNW000000000 and JAVVNV000000000 and in the National Genomics Data Center BioProject database (https://ngdc.cncb.ac.cn/bioproject/) under the accession number PRJCA019650. Genome assemblies with annotations and results of ChIP–seq and DNase-seq can be accessed at FigShare (https://figshare.com/projects/Origin_and_evolution_of_the_triploid_cultivated_banana_genome/178041). Raw data used for the assemblies, including PacBio, Illumina and Hi-C data, are available through the Sequence Read Archive of the National Centre for Biotechnology Information (NCBI) under the BioProject PRJNA1017453 with SRA accessions from SRR23425440 to SRR23425472 and from SRR23885547 to SRR23885549. Fifty-eight RNA-seq datasets were downloaded from NCBI BioProject accessions PRJNA381300, PRJNA394594 and PRJNA598018. DNA methylation data were downloaded from NCBI BioProject PRJNA381300.Most fresh bananas belong to the Cavendish and Gros Michel subgroups. Here, we report chromosome-scale genome assemblies of Cavendish (1.48 Gb) and Gros Michel (1.33 Gb), defining three subgenomes, Ban, Dh and Ze, with Musa acuminata ssp. banksii, malaccensis and zebrina as their major ancestral contributors, respectively. The insertion of repeat sequences in the Fusarium oxysporum f. sp. cubense (Foc) tropical race 4 RGA2 (resistance gene analog 2) promoter was identified in most diploid and triploid bananas. We found that the receptor-like protein (RLP) locus, including Foc race 1-resistant genes, is absent in the Gros Michel Ze subgenome. We identified two NAP (NAC-like, activated by apetala3/pistillata) transcription factor homologs specifically and highly expressed in fruit that directly bind to the promoters of many fruit ripening genes and may be key regulators of fruit ripening. Our genome data should facilitate the breeding and super-domestication of bananas.The National Natural Science Foundation of China, Construction of Plateau Discipline of Fujian Province, the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program and from Ghent University (Methusalem funding).http://www.nature.com/ng2024-06-11hj2024BiochemistryGeneticsMicrobiology and Plant PathologySDG-02:Zero Hunge

    Вихретоковый анизотропный термоэлектрический первичный преобразователь лучистого потока

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    Представлена оригинальная конструкция первичного преобразователя лучистого потока, который может служить основой для создания приемника неселективного излучения с повышенной чувствительностью
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