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Project page for Dyn-E: Local Appearance Editing of Dynamic Neural Radiance Fields
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2026-02-24 06:38:07
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Dyn-E Dyn-E : Local Appearance Editing of Dynamic Neural Radiance Fields arXiv 2023 Anonymous Abstract Recently, the editing of neural radiance fields (NeRFs) has gained considerable attention, but most prior works focus on static scenes while research on the appearance editing of dynamic scenes is relatively lacking. In this paper, we propose a novel framework to edit the local appearance of dynamic NeRFs by manipulating pixels in a single frame of training video. Specifically, to locally edit the appearance of dynamic NeRFs while preserving unedited regions, we introduce a local surface representation of the edited region, which can be inserted into and rendered along with the original NeRF and warped to arbitrary other frames through a learned invertible motion representation network. By employing our method, users without professional expertise can easily add desired content to the appear...
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