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Found 4 papers, 1 papers with code
Lagrangian Hashing for Compressed Neural Field Representations
We present Lagrangian Hashing, a representation for neural fields combining the characteristics of fast training NeRF methods that rely on Eulerian grids (i. e.~InstantNGP), with those that employ points equipped with features as a way to represent information (e. g. 3D Gaussian Splatting or PointNeRF).
Stereo-Knowledge Distillation from dpMV to Dual Pixels for Light Field Video Reconstruction
Dual pixels contain disparity cues arising from the defocus blur.
BANF: Band-limited Neural Fields for Levels of Detail Reconstruction
Largely due to their implicit nature, neural fields lack a direct mechanism for filtering, as Fourier analysis from discrete signal processing is not directly applicable to these representations.
Synthesizing Light Field Video from Monocular Video
Hence, we propose a self-supervised learning-based algorithm for LF video reconstruction from monocular videos.
