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Scene Processing With Machine Learnable and Semantically Parametrized Representations RENEWAL

Scene Processing With Machine Learnable and Semantically Parametrized Representations RENEWAL
使用机器学习和语义参数化表示进行场景处理 RENEWAL
批准号:
MR/Y033884/1
负责人:
Ahmet Oztireli
金额:
$75.36万
依托单位:
依托单位国家:
英国
项目类别:
Fellowship
财政年份:
2025
资助国家:
英国
项目状态:
未结题
起止时间:
2025 至 --

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中文摘要
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英文摘要
Generative artificial intelligence has made a significant leap in developing intuitive natural language based computer interfaces via large language models, and realistic image and video generation from text inputs. These have already started revolutionising creation and editing of code, text, images, videos, presentations, and many other digital media. We will extend these techniques to scene creation and processing by relying on the techniques we have been developing over the years. We will develop text-to-scene models for easy creation, intuitive control, and conversational capture of 3D objects and scenes. We will deploy these models to the new generation of extended reality devices with advanced displays, optics, sensors, and processing units to build a scene creation and editing system that uses voice and brain signals as inputs.
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Scene Processing with Machine Learnable and Semantically Parametrized Scene Representations
  • 批准号:
    MR/T043229/1
  • 项目类别:
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  • 资助金额:
    $154.77万
  • 财政年份:
    2021
  • 负责人:
    Ahmet Oztireli
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