Lightplane: Highly-Scalable Components for Neural 3D Fields
Contemporary 3D research, particularly in reconstruction and generation,
heavily relies on 2D images for inputs or supervision. However, current designs
for these 2D-3D mapping are memory-intensive, posing a significant bottleneck
for existing methods and hindering new applications. In response, we propose a
pair of highly scalable components for 3D neural fields: Lightplane Render and
Splatter, which significantly reduce memory usage in 2D-3D mapping. These
innovations enable the processing of vastly more and higher resolution images
with small memory and computational costs. We demonstrate their utility in
various applications, from benefiting single-scene optimization with
image-level losses to realizing a versatile pipeline for dramatically scaling
3D reconstruction and generation. Code:
https://github.com/facebookresearch/lightplane.
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Ang Cao
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2024-05-02T08:37:10.576Z
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Ang Cao
user
AACEE
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Justin Johnson
6631ca1a351231c4280963d3
Andrea Vedaldi
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David Novotny
Lightplane: Highly-Scalable Components for Neural 3D Fields
Contemporary 3D research, particularly in reconstruction and generation,
heavily relies on 2D images for inputs or supervision. However, current designs
for these 2D-3D mapping are memory-intensive, posing a significant bottleneck
for existing methods and hindering new applications. In response, we propose a
pair of highly scalable components for 3D neural fields: Lightplane Render and
Splatter, which significantly reduce memory usage in 2D-3D mapping. These
innovations enable the processing of vastly more and higher resolution images
with small memory and computational costs. We demonstrate their utility in
various applications, from benefiting single-scene optimization with
image-level losses to realizing a versatile pipeline for dramatically scaling
3D reconstruction and generation. Code:
https://github.com/facebookresearch/lightplane.
Lightplane Render and Splatter components reduce memory usage in 2D-3D mapping for 3D neural fields, enabling efficient processing and scalable reconstruction and generation.
3D neural fields Lightplane Render Splatter 2D-3D mapping memory usage