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公开(公告)号:US20250111588A1
公开(公告)日:2025-04-03
申请号:US18479261
申请日:2023-10-02
Applicant: Nvidia Corporation
Inventor: Karsten Julian Kreis , Maria Shugrina , Ming-Yu Liu , Or Perel , Sanja Fidler , Towaki Alan Takikawa , Tsung-Yi Lin , Xiaohui Zeng
Abstract: Systems and methods of the present disclosure include interactive editing for generated three-dimensional (3D) models, such as those represented by neural radiance fields (NeRFs). A 3D model may be presented to a user in which the user may identify one or more localized regions for editing and/or modification. The localized regions may be selected and a corresponding 3D volume for that region may be provided to one or more generative networks, along with a prompt, to generate new content for the localized regions. Each of the original NeRF and the newly generated NeRF for the new content may then be combined into a single NeRF for a combined 3D representation with the original content and the localized modifications.
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公开(公告)号:US20240161403A1
公开(公告)日:2024-05-16
申请号:US18232279
申请日:2023-08-09
Applicant: NVIDIA Corporation
Inventor: Chen-Hsuan Lin , Tsung-Yi Lin , Ming-Yu Liu , Sanja Fidler , Karsten Kreis , Luming Tang , Xiaohui Zeng , Jun Gao , Xun Huang , Towaki Takikawa
CPC classification number: G06T17/20 , G06T3/40 , G06T15/04 , G06T17/005 , G06T19/20
Abstract: Text-to-image generation generally refers to the process of generating an image from one or more text prompts input by a user. While artificial intelligence has been a valuable tool for text-to-image generation, current artificial intelligence-based solutions are more limited as it relates to text-to-3D content creation. For example, these solutions are oftentimes category-dependent, or synthesize 3D content at a low resolution. The present disclosure provides a process and architecture for high-resolution text-to-3D content creation.
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