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K-Planes: Explicit Radiance Fields in Space, Time, and Appearance

Computer Science

K-Planes: Explicit Radiance Fields in Space, Time, and Appearance

S. Fridovich-keil, G. Meanti, et al.

Discover k-planes, an innovative white-box model that transforms the representation of radiance fields in any dimension. Developed by a talented team of authors including Sara Fridovich-Keil and Giacomo Meanti, this model achieves remarkable efficiency, offering up to 1000x compression while maintaining impressive fidelity across varying appearances. Join us in exploring this groundbreaking approach that seamlessly transitions from static to dynamic scenes.

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~3 min • Beginner • English
Abstract
We introduce k-planes, a white-box model for radiance fields in arbitrary dimensions. Our model uses d choose 2 planes to represent a d-dimensional scene, providing a seamless way to go from static (d = 3) to dynamic (d = 4) scenes. This planar factorization makes adding dimension-specific priors easy, e.g. temporal smoothness and multi-resolution spatial structure, and induces a natural decomposition of static and dynamic components of a scene. We use a linear feature decoder with a learned color basis that yields similar performance as a nonlinear black-box MLP decoder. Across a range of synthetic and real, static and dynamic, fixed and varying appearance scenes, k-planes yields competitive and often state-of-the-art reconstruction fidelity with low memory usage, achieving 1000x compression over a full 4D grid, and fast optimization with a pure PyTorch implementation.
Publisher
arXiv
Published On
Mar 24, 2023
Authors
Sara Fridovich-Keil, Giacomo Meanti, Frederik Rahbaek Warburg, Benjamin Recht, Angjoo Kanazawa
Tags
k-planes
radiance fields
dimensional scenes
temporal smoothness
multi-resolution
reconstruction fidelity
memory usage
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