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Nerf: Neural radiance field in 3d vision, a comprehensive review
Gaussianeditor: Editing 3d gaussians delicately with text instructions
Recently impressive results have been achieved in 3D scene editing with text instructions
based on a 2D diffusion model. However current diffusion models primarily generate images …
based on a 2D diffusion model. However current diffusion models primarily generate images …
Tensorf: Tensorial radiance fields
We present TensoRF, a novel approach to model and reconstruct radiance fields. Unlike
NeRF that purely uses MLPs, we model the radiance field of a scene as a 4D tensor, which …
NeRF that purely uses MLPs, we model the radiance field of a scene as a 4D tensor, which …
Decomposing nerf for editing via feature field distillation
Emerging neural radiance fields (NeRF) are a promising scene representation for computer
graphics, enabling high-quality 3D reconstruction and novel view synthesis from image …
graphics, enabling high-quality 3D reconstruction and novel view synthesis from image …
Clip-nerf: Text-and-image driven manipulation of neural radiance fields
We present CLIP-NeRF, a multi-modal 3D object manipulation method for neural radiance
fields (NeRF). By leveraging the joint language-image embedding space of the recent …
fields (NeRF). By leveraging the joint language-image embedding space of the recent …
Delicate textured mesh recovery from nerf via adaptive surface refinement
Abstract Neural Radiance Fields (NeRF) have constituted a remarkable breakthrough in
image-based 3D reconstruction. However, their implicit volumetric representations differ …
image-based 3D reconstruction. However, their implicit volumetric representations differ …