1 citations · 1 across the 7 of their papers we have counts for
6 papers · 1 filter
Semantic Foam: Unifying Spatial and Semantic Scene Decomposition
Amr Sharafeldin, Shrisudhan Govindarajan, Thomas Walker +4
Modern scene reconstruction methods, such as 3D Gaussian Splatting, deliver photo-realistic novel view synthesis at real-time speeds, yet their adoption in interactive graphics app…
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…
Stereo-Knowledge Distillation from dpMV to Dual Pixels for Light Field Video Reconstruction
Aryan Garg, Raghav Mallampali, Akshat Joshi +2
Dual pixels contain disparity cues arising from the defocus blur. This disparity information is useful for many vision tasks ranging from autonomous driving to 3D creative realism.…
BANF: Band-limited Neural Fields for Levels of Detail Reconstruction
Ahan Shabanov, Shrisudhan Govindarajan, Cody Reading +4
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 r…