63 citations · 143 across the 20 of their papers we have counts for
32 papers
Power Foam: Unifying Real-Time Differentiable Ray Tracing and Rasterization
Shrisudhan Govindarajan, Daniel Rebain, Dor Verbin +3
We introduce a differentiable 3D representation that unifies the ray tracing capabilities of foam-based ray tracing with the efficiency of modern rasterization pipelines. While pri…
NoKSR: Kernel-Free Neural Surface Reconstruction via Point Cloud Serialization
Zhen Li, Weiwei Sun, Shrisudhan Govindarajan +4
We present a novel approach to large-scale point cloud surface reconstruction by developing an efficient framework that converts an irregular point cloud into a signed distance fie…
Radiant Foam: Real-Time Differentiable Ray Tracing
Shrisudhan Govindarajan, Daniel Rebain, Kwang Moo Yi +1
Research on differentiable scene representations is consistently moving towards more efficient, real-time models. Recently, this has led to the popularization of splatting methods,…
Lagrangian Hashing for Compressed Neural Field Representations
Shrisudhan Govindarajan, Zeno Sambugaro, Akhmedkhan +7
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 th…
SparsePose: Sparse-View Camera Pose Regression and Refinement
Samarth Sinha, Jason Y. Zhang, Andrea Tagliasacchi +2
Camera pose estimation is a key step in standard 3D reconstruction pipelines that operate on a dense set of images of a single object or scene. However, methods for pose estimation…
nerf2nerf: Pairwise Registration of Neural Radiance Fields
Lily Goli, Daniel Rebain, Sara Sabour +2
We introduce a technique for pairwise registration of neural fields that extends classical optimization-based local registration (i.e. ICP) to operate on Neural Radiance Fields (Ne…